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ft_interpolatenan.m
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ft_interpolatenan.m
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function dataout = ft_interpolatenan(cfg, datain)
% FT_INTERPOLATENAN interpolates data that contains segments of nans
% obtained by replacing artifactual data with nans using, for example, FT_REJECTARTIFACT,
% or by redefining trials with FT_REDEFINETRIAL resulting in trials with
% gaps.
%
% Use as
% outdata = ft_interpolatenan(cfg, indata)
% where indata is data as obtained from FT_PREPROCESSING
% and cfg is a configuratioun structure that should contain
%
% cfg.method = string, interpolation method, see HELP INTERP1 (default = 'linear')
% cfg.prewindow = value, length of data prior to interpolation window, in seconds (default = 1)
% cfg.postwindow = value, length of data after interpolation window, in seconds (default = 1)
%
%
% To facilitate data-handling and distributed computing with the peer-to-peer
% module, this function has the following options:
% cfg.inputfile = ...
% cfg.outputfile = ...
% If you specify one of these (or both) the input data will be read from a *.mat
% file on disk and/or the output data will be written to a *.mat file. These mat
% files should contain only a single variable, corresponding with the
% input/output structure.
%
% See also FT_REJECTARTIFACT, FT_REDEFINETRIAL
% Copyright (C) 2003-2011, Jan-Mathijs Schoffelen & Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip 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.
%
% FieldTrip 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 FieldTrip. If not, see <http://www.gnu.org/licenses/>.
%
% $Id$
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% the initial part deals with parsing the input options and data
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% these are used by the ft_preamble/ft_postamble function and scripts
ft_revision = '$Id$';
ft_nargin = nargin;
ft_nargout = nargout;
% do the general setup of the function
ft_defaults
ft_preamble init
ft_preamble debug
ft_preamble loadvar datain
ft_preamble provenance datain
ft_preamble trackconfig
% the ft_abort variable is set to true or false in ft_preamble_init
if ft_abort
return
end
% check if the input data is valid for this function
datain = ft_checkdata(datain, 'datatype', {'raw+comp', 'raw'}, 'feedback', 'yes', 'hassampleinfo', 'yes');
% check if the input is valid
cfg = ft_checkconfig(cfg, 'allowedval',{'method','nearest','linear','spline','pchip','cubic','v5cubic'});
cfg = ft_checkopt(cfg, 'prewindow', 'numericscalar');
cfg = ft_checkopt(cfg, 'postwindow', 'numericscalar');
% get the options
method = ft_getopt(cfg, 'method', 'linear'); % default is linear
prewindow = ft_getopt(cfg, 'prewindow', 1); % default is 1 second
postwindow = ft_getopt(cfg, 'postwindow', 1); % default is 1 seconds
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% the actual computation is done in the middle part
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
dataout = datain;
ntrl = numel(datain.trial);
prewindow = round(prewindow * datain.fsample); % Express window in samples
postwindow = round(postwindow * datain.fsample); % Express window in samples
% Let users know that the interpolation will start and initialize the
% progress indicator
fprintf('Initializing %s interpolation of %d trials\n',method,ntrl);
ft_progress('init', 'etf');
for i=1:ntrl
ft_progress(i/ntrl, 'Processing trial %d out of %d',i,ntrl);
nchan = size(datain.trial{i},1);
replace = isnan(datain.trial{i}); % Find samples that have been replaced by nans
if any(replace(:)) % Check whether any values should be interpolated
[idx_start_r, idx_start_c] = find(diff(replace,[],2)==1); % Determine onset of nan-chunk
[dum, idx_end_c] = find(diff(replace,[],2)==-1); % Determine offset of nan-chunk
idx_start_c = idx_start_c + 1; % correct for shift due to using diff
% Loop across found nan-chunks
for j=1:size(idx_start_c,1)
sample_window = [idx_start_c(j)-prewindow:idx_start_c(j)-1 idx_end_c(j)+1:idx_end_c(j)+postwindow]; % Indices of time-points used for interpolation
if any(sample_window<1) || any(sample_window>size(datain.trial{i},2)) % Check whether sampling window falls within data range
ft_warning('Sample window partially outside of data-range, using less samples');
sample_window(sample_window<1|sample_window>size(datain.trial{i},2))=[];
elseif any(isnan(datain.trial{i}(idx_start_r(j),sample_window))) % Check whether sampling window overlaps with other chunk of nans
error('Sample window overlaps with other chunk of nans');
end;
fill_window = idx_start_c(j):idx_end_c(j); % Indices of time-points that will be interpolated
fill = interp1(sample_window, datain.trial{i}(idx_start_r(j),sample_window),fill_window,method); % Interpolation
dataout.trial{i}(idx_start_r(j),fill_window)=fill; % Add interpolated segments to dataout
end;
end;
end; % i=1:ntrl
ft_progress('close');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Cleanup
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
ft_postamble debug
ft_postamble trackconfig
ft_postamble previous datain
ft_postamble provenance dataout
ft_postamble history dataout
ft_postamble savevar dataout