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parameterCharacterization2.m
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parameterCharacterization2.m
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function out = parameterCharacterization(t,f)
global signalact tsignalact tsignal tmax noise fitting signal dfb dff plt tdrift fdrift driftmod driftmod2 tdriftswitch tend driftdermod driftdermod2 sigma indactmin inddrift inddriftclean indactminclean
global wint
global dev_thresh
%estimate instrumental/experimental drift in the first 8 seconds
%in order to characterize the noise of setup and determine if there
%a response > 4*StdDev within a reasonable time window (25% of the total recording)
ind=t<8;
%lets rezero around the first datapoint:
offset=f(1);
f=f-f(1);
signal=f;
tsignal=t;
function plotEmpty(ttl)
cf(1);
% set(gcf, 'Position', get(0, 'Screensize'));
% set(gcf,'units','normalized','outerposition',[0 0 1 1]);
h=plot(t,f+offset,'.b',t,fufine(:,1)+offset,'-r',t,f(spike)+offset,'xc');
set(h(2),'linewidth',2);
set(gca,'FontSize',18);
xlabel('Time (s)');
ylabel('Fluorescence (A.U.)');
legend('Data','TV Data Estimate');
set(gcf,'Color','w');
ht=title(ttl);
set(ht,'FontSize',8);
end
function cornerLegend(hleg)
set(hleg,'fontsize',10);
posleg=get(hleg,'Position');
set(hleg,'Position',[0 1-posleg(4) posleg(3) posleg(4)]);
set(hleg,'units','pixels')
posleg=get(hleg,'Position');
set(hleg,'Position',[2 posleg(2)-2 posleg(3) posleg(4)]);
end
function annotateActivation()
x=x_to_norm(actfit.ton,actfit.ton);
x(x>1)=1;
x(x<0)=0;
y=ylim();
y=y_to_norm(y(2),actsol(find(t>=actfit.ton,1)));
y(y>1)=1;
y(y<0)=0;
annotation('textarrow',x,y,'String',['t_{switch} = ' num2str(actfit.ton) ' s'])
end
function annotateResponse()
x=x_to_norm(tdec,tdec);
y=y_to_norm(rmax,r5050);
annotation('line',x,y,'LineStyle',':','Color','green');
% x=x_to_norm(respfit.ton,respfit.ton);
% ton=respfit.ton;
% y=y_to_norm(0.5*fmax,respfit(ton));
% annotation('textarrow',x,y,'String',['t_{on} = ' num2str(respfit.ton) ' s'])
%
x=x_to_norm(out.ton,tdec);
y=ylim();
y=y_to_norm(rmax,rmax);
annotation('textarrow',x,y,'String','')
x=x_to_norm(out.ton,out.ton);
y=ylim();
y=y_to_norm(y(2),f(find(t==out.ton,1)));
annotation('textarrow',x,y,'String',{['t_{act} = ' num2str(out.ton) ' s'];['Amplitude = ' num2str(out.amplitude) ' A.U.']},'HorizontalAlignment','left')
%
if isfield(out,'decaytime')
idecay0=idecay0-1;
idecay=find(t>=decay,1);
x=x_to_norm(decay,decay);
y=ylim;
y=y_to_norm(y(2),ffit(idecay-idecay0));
annotation('textarrow',x,y,'String',{['t_{0,decay} = ' num2str(decay) ' s'] ;[' \tau_{decay} = ' num2str(out.decaytime) ' s']},'HorizontalAlignment','right');
mt=min(decay+out.decaytime,t(end));
idecay2=find(t>=(mt),1);
x=x_to_norm(mt,mt);
y=ylim;
y=y_to_norm(ffit(idecay-idecay0)+0.75*(y(2)-ffit(idecay-idecay0)),ffit(idecay2-idecay0));
annotation('textarrow',x,y,'String','');
x=x_to_norm(decay,mt);
y=ylim;
y=y_to_norm(ffit(idecay-idecay0)+0.75*(y(2)-ffit(idecay-idecay0)),ffit(idecay-idecay0)+0.75*(y(2)-ffit(idecay-idecay0)));
annotation('line',x,y);
end
end
% cf(1);plot(t,f);drawnow;
tic;
try
[fu2,spike2,imu2,fufine2,noise2] = TVRegSpikeRemoveMultiL1BiCont2(f, 3, [], 'large', 1e-3, 1 / length(f),1, 0,0);
[fu,spike,imu,fufine,noise] = TVRegSpikeRemove(f, 3, 0,0);
catch e
out=[];
display('problem ~100')
disp(e)
return;
end
if toc > 15
disp('long one');
dt=datestr(now,'mmmm_dd_yyyy_HH.MM.SS.FFF');
save(['long_one.' dt '.mat'],'t','f');
end
dt=mean(diff(t));
tend=t(find(~spike,1,'last'));
if isempty(imu)
out=[];
disp('No Discernible Response: Derivative did not yield and activation estimates');
return;
end
yp = fu(:,2);
%if monotonically decreasing function or derivative
if sum(yp>0)<6
out=[];
disp('No Discernible Response: Monotonically decreasing drift.');
return;
end
% hh
% yp = TVRegDiff(f, iters, 0.001 , [], 'small', 1e-6, 0.01, 0, 0 );
% %beginning of estimate cannot be trusted
% yp(1:iters)=yp(iters);
%
% % cf(55);plot(yp);
% % yp=yp(1:end-1);
%find the first significant upstroke
ndrift=2;
% =find(yp(ndrift:end-1)>0&(yp(ndrift:end-1)-yp(ndrift-1:end-2)>var(yp)|(yp(ndrift:end-1)>yp(ndrift-1:end-2)&yp(ndrift:end-1)==max(yp(ndrift:end-1)))),1)+ndrift;
ipmax2=find(yp(ndrift:end-1)>0&(yp(ndrift:end-1)-yp(ndrift-1:end-2)>std(yp)|(yp(ndrift:end-1)>yp(ndrift-1:end-2)&yp(ndrift:end-1)==max(yp(ndrift:end-1)))),1)+ndrift;
ipmax2=find(yp>std(yp),1);
ipmax2=imu(1);
% [ypmax,ipmax]=max(yp);
[ypmin,ipmin]=min(abs(yp(ipmax2+1:end)));
ipmin2=find(abs(yp(ipmax2+1:end))<noise/2,1);
if ~isempty(ipmin2)
ipmin=min(ipmin,ipmin2);
end
ipmin=ipmin+ipmax2-1;
yp1=yp(1:ipmax2);
yp2=yp(ipmin:end);
%only look at positive derivatives
yp0=find(yp(1:ipmax2)<0,1,'last');
%if we crossed zero get rid of those points before the crossing
if ~isempty(yp0) && yp0<ipmax2
yp1=yp1(yp0:end);
else
yp0=2;
end
%shift derivative scale to baseline
yp1=yp1-min(yp1);
ypmax1=yp1(end);
% yp2=yp2-max(yp2);
yp2=abs(yp2-yp2(end));
ypmin2=min(yp2);
% indactmin=find(yp1<var(yp1),1,'last')+yp0;
indactmin=int16(find(yp(yp0:ipmax2)/yp(ipmax2)<std(yp(1:yp0)/yp(ipmax2)),1,'last'))+(yp0-1);
if isempty(indactmin)
indactmin=int16(find(yp(yp0:ipmax2)/yp(ipmax2)<std(yp(yp0:ipmax2)/yp(ipmax2)),1,'last'))+(yp0-1);
if isempty(indactmin)
indactmin=2;
end
else
indactmin=min(indactmin,int16(find(yp(yp0:ipmax2)<var(yp(yp0:ipmax2)),1,'last'))+(yp0-1));
end
nn=3;
inddrift=[];
while nn>=0 && isempty(inddrift);
inddrift=find((yp2-mean(yp2))>nn*std(yp2),1,'last')+ipmin;
nn=nn-1;
end
if isempty(inddrift)
inddrift=find(abs(yp2-mean(yp2))>std(yp2),1,'last')+ipmin;
inddrift=min(find(~spike,2,'last'));
end
% cf(99);
% subplot(3,1,1);
% plot(yp);
% subplot(3,1,2);
% plot(yp1);
% subplot(3,1,3);
% plot(yp2);
try
[fmax,indmax]=max(fu(:,2));
mxu=zeros(size(imu));
mnu=zeros(size(imu));
di=zeros(size(imu));
for ii=1:length(imu)
i0n=find(fu(1:imu(ii),2)<=0,1,'last');
if isempty(i0n)
i0n=1;
end
mnu(ii)=fu(i0n,1);
i0x=find(fu(imu(ii):end,2)<=0,1)+imu(ii)-1;
if ~isempty(i0x)
mxu(ii)=fu(i0x,1);
mnu(ii)=mnu(ii)+mean(fu([max(i0n-1,1),i0n],2))*(i0x-i0n)/(length(t)*dt);
di(ii)=(i0x-i0n);
else
mxu(ii)=-Inf;
end
end
catch e
display('problem ~250')
disp(e)
end
% [~,ii]=max((mxu-mnu));
if sum(isfinite(mxu))>2
mxu=mxu(isfinite(mxu));
mnu=mnu(isfinite(mxu));
di=di(isfinite(mxu));
ii=[];
nn=3;
try
mu=(mxu-mnu)./di;
nu=(mxu-mnu);
mu(nu<mean(nu)-std(nu))=0;
while nn<=3&&nn>0&&isempty(ii)
ii=find(mu>mean(mu)-nn*std(mu)&mu~=0,1);
nn=nn-1;
end
if isempty(ii)
ii=length(imu);
end
catch e
display('problem ~280')
disp(e)
end
else
[~,ii]=max((mxu-mnu));
end
try
indmax2=find(fu(imu(ii)+1:end,2)/length(t)<=-noise,1)+imu(ii)+1;
% [fmax,indmax2]=max(fu(imu(ii):indmax2,1));
catch e
display('problem ~290')
disp(e);
end
try
% indmax=imu(ii)+indmax2-1;
indmax=indmax2;
catch e
display('problem ~300')
getReport(e)
end
if isempty(indmax)
[~,indmax]=max(fu(:,1));
end
fmax=fu(indmax,1);
tmax=t(min(indmax+1,length(t)));
indmax0=indmax;
fact=f(~spike(1:indmax));
tact=t(~spike(1:indmax));
[fmin,indmin]=min(fact);
% indact2=find(fact(tact>t(indmin))-fmin>=0.1*(fmax-fmin),1)+indmin;
%this only works with little noise...needs to mad more robust
% indact=find(fact(tact>t(indmin))-fmin>=0.3*(fmax-fmin),1)+indmin;
%
% if ~isempty(indact)
% indactmin=max(int16(indactmin),int16(0.8*indact));
% end
driftind=[1:max(2,indactmin),min(inddrift,length(t)-1):length(t)];
driftind=driftind(~spike(driftind));
tdrift=t(driftind);
fdrift=f(driftind);
actdriftind=[1:indmax,min(inddrift,length(t)-1):length(t)];
sigma=mean(abs(fu(~spike(1:indactmin),1)-f(~spike(1:indactmin))));
tact2dirty=t(actdriftind);
ypact=fufine(actdriftind,2)/(length(t)*dt);
wyp=exp(-((f(actdriftind)-fufine(actdriftind,1)).^4)/(sigma^4));
wyp(indactmin:indmax)=1;
actdriftind=actdriftind(~spike(actdriftind));
fact2=f(actdriftind);
tact2=t(actdriftind);
tactmin=t(indactmin);
ypdrift=fu(driftind,2)/(length(t)*dt);
ypdriftmin=min(min(ypdrift),0);
ypdriftmax=max(max(ypdrift),0);
maxA=2*(max(f)-min(f));
lact=[-maxA,-maxA,-Inf,-Inf,0,0,0,-Inf];
uact=[maxA,maxA,Inf,Inf,t(end),t(end),t(end),Inf];
sigma=mean(abs(fu(~spike(1:indactmin),1)-f(~spike(1:indactmin))));
ld=[-maxA,-maxA,ypdriftmin,ypdriftmin,0,0,0,-Inf];
ud=[maxA,maxA,ypdriftmax,ypdriftmax,t(end),t(end),t(end),Inf];
% if ypdrift(1)<0;
% ud(1)=sigma;
% u(1)=sigma;
% else
% ld(1)=-sigma;
% l(1)=-sigma;
% end
tdriftswitch=t(ipmax2);
tdriftswitch0=t(ipmax2);
inddriftclean=find(~spike(inddrift:end),1)+(inddrift-1-sum(spike(1:inddrift-1+find(~spike(inddrift:end),1))));
driftmod=@(A1,A2,m1,m2,tau1,tau2,z,x) [A1*(1-exp(-x(x<=tdriftswitch)/tau1))+m1*x(x<=tdriftswitch)+z;A1*(1-exp(-x(x>tdriftswitch)/tau1))+A2*(1-exp(-(x(x>tdriftswitch)-tdriftswitch)/tau2))+m2*(x(x>tdriftswitch)-tdriftswitch)+m1*x(x>tdriftswitch)+z];
driftmod2=@(A1,A2,m1,m2,tau1,tau2,tdriftswitch,z,x) [A1*(1-exp(-x(x<=tdriftswitch)/tau1))+m1*x(x<=tdriftswitch)+z;A1*(1-exp(-x(x>tdriftswitch)/tau1))+A2*(1-exp(-(x(x>tdriftswitch)-tdriftswitch)/tau2))+m2*(x(x>tdriftswitch)-tdriftswitch)+m1*x(x>tdriftswitch)+z];
driftdermod=@(A1,A2,m1,m2,tau1,tau2,tdriftswitch,x) [(A1/tau1)*(exp(-x(x<=tdriftswitch)/tau1))+m1;(A1/tau1)*(exp(-x(x>tdriftswitch)/tau1))+(A2/tau2)*(exp(-(x(x>tdriftswitch)-tdriftswitch)/tau2))+m2+m1];
d2mod=@(A1,A2,m1,m2,tau1,tau2,tdriftswitch,z,x)[driftmod2(A1,A2,m1,m2,tau1,tau2,tdriftswitch,z,x(1:floor(length(x)/2)));driftdermod(A1,A2,m1,m2,tau1,tau2,tdriftswitch,x(floor(length(x)/2)+1:end))];
indactminclean=indactmin-sum(spike(1:indactmin));
sact=[(f(end)-f(1)),(f(inddrift)-f(indactmin))+ypdrift(indactminclean)*((t(inddrift)-tdriftswitch))+(f(end)-f(1))*(exp(-t(inddrift)/t(indactmin))),ypdrift(indactminclean),ypdrift(end), t(indactmin),(t(inddrift)-tdriftswitch)/5,tdriftswitch0,0];
sd=[(f(end)-f(1)),(f(inddrift)-f(indactmin))+ypdrift(indactminclean)*((t(inddrift)-tdriftswitch)),ypdrift(indactminclean),ypdrift(end), t(indactmin),(t(inddrift)-tdriftswitch)/5,tdriftswitch0,0];
try
driftfit=fit(tdrift,fdrift,driftmod2,'Startpoint',sact,'Lower',lact,'Upper',uact);
%
%
% cf(99);
% subplot(2,1,1);
% plot(t,f,'-b',t(spike),f(spike),'xg',t,fufine(:,1),'-k');
% subplot(2,1,2);
% % plot(t,f,'-b',tdrift,fdrift,'or',t(indactmin:ipmax2),f(indactmin:ipmax2),'og',t,driftfit(t),'-k',t,fufine(:,1),'-b',t,fu(:,1),'-c');
% plot(t,f,'-b',tdrift,fdrift,'or',t(indactmin:ipmax2),f(indactmin:ipmax2),'og',t,driftfit(t),'-k');
% ylim([min(f),max(f)]);
c=differentiate(driftfit,tdrift)-ypdrift;
d=double(ones(size(c)));
cr=find((c(1:end-1)>0&c(2:end)<0)|(c(1:end-1)<0&c(2:end)>0),1,'last');
d(1:indactminclean)=exp(-((abs(c(1:indactminclean))).^2)/(mean(abs(c(1:indactminclean))))^2);
d(indactminclean+1:end)=exp(-((abs(c(indactminclean+1:end))).^2)/(mean(abs(c(indactminclean+1:end))))^2);
d(indactminclean+1:end)=d(indactminclean+1:end)*sum(d(1:indactminclean))/sum(d(indactminclean+1:end));
% dadj(indactminclean+1:end)=d(indactminclean+1:end)*sum(d(1:indactminclean))/sum(d(indactminclean+1:end));
dadj=d;
d2fit=fit([tdrift;tdrift],[fdrift;ypdrift],d2mod,'Startpoint',sd,'Lower',ld,'Upper',ud,'Weights',[dadj;dadj]);
catch e
display('problem ~430')
disp('not enough drift')
end
df=d2fit;
c=driftdermod(df.A1,df.A2,df.m1,df.m2,df.tau1,df.tau2,df.tdriftswitch,tdrift)-ypdrift;
d=double(ones(size(c)));
cr=find((c(1:end-1)>0&c(2:end)<0)|(c(1:end-1)<0&c(2:end)>0),1,'last');
d(1:indactminclean)=exp(-((abs(c(1:indactminclean))).^2)/(mean(abs(c(1:indactminclean))))^2);
d(indactminclean+1:end)=exp(-((abs(c(indactminclean+1:end))).^2)/(mean(abs(c(indactminclean+1:end))))^2);
d(indactminclean+1:end)=d(indactminclean+1:end)*sum(d(1:indactminclean))/sum(d(indactminclean+1:end));
% dadj(indactminclean+1:end)=d(indactminclean+1:end)*sum(d(1:indactminclean))/sum(d(indactminclean+1:end));
dadj=d;
% if d2fit.A2>0
% ld(2)=-sigma;
% else
% ud(2)=sigma;
% end
% cf(77);plot(driftderfit,tdrift,ypdrift);
hold on
% cf(66);plot(t,driftmod2(df.A1,df.A2,df.m1,df.m2,df.tau1,df.tau2,df.tdriftswitch,df.z,t),t,f,tdrift,fdrift,'ob');
% ylim([min(fdrift) max(fdrift)]);
d2=d2fit([tdrift;tdrift]);
fd=d2(1:length(tdrift));
fpd=d2(length(tdrift)+1:end);
% cf(188);plot(tdrift,fd,'-r',tdrift,fdrift,'-b',tdrift,fpd,':r',tdrift,ypdrift,':b');
noise=mean(abs(fu(~spike)-f(~spike)));
driftsol=driftmod2(df.A1,df.A2,df.m1,df.m2,df.tau1,df.tau2,df.tdriftswitch,df.z,t);
if ~isempty(plt) && plt
cf(1);
% set(gcf,'units','normalized','outerposition',[0 0 1 1]);
h=plot(t(~spike),f(~spike)+offset,'.b',t(spike),f(spike)+offset,'xc',tdrift,fdrift+offset,'.r',t(indactmin:ipmax2),f(indactmin:ipmax2)+offset,'.g',t,fufine(:,1)+offset,'-b',t,driftsol+offset,'-k');
ylim([min(f),max(f)]+offset);
xlim([min(t),max(t)]);
set(gca,'FontSize',18);
xlabel('Time (s)');
ylabel('Fluorescence (A.U.)');
set(h,'linewidth',2);
set(gcf,'Color','w');
hlabel=h;
hleg=legend(hlabel,'Data','Noise Spike','Estimated Drift','Estimated Activation','TV Data Estimate','Initial Drift Fitting','Location','NorthWest');
cornerLegend(hleg);
end
%if the estimated "response" is not significantly different
%from noise (4*StdDev) then there is no discernable reponse
if sum(diff(find(f-driftsol>sqrt(2)*noise))==1)<6
% cf(99);
%
% plot(t,f+offset);
%
% out=[];
disp('Predicted Response not Discernable from Noise.');
return;
else
%there is a significant response!
out=struct();
%first we will estimate the time of receptor activation (ton).
%for this purpose we will truncate the signal when it reaches its
%maximal value and fit the beginning of the signal with a
%piecewise function which switches from being a simple linear
%to the sum of the same linear function and a hill function.
minn=1;
maxn=log(realmax)/(2*log(2*t(end)));
maxm=abs(max(f)-min(f))/t(end);
maxm=max(abs(fu(:,2)/(dt*length(t))));
dff=[f(2:end)-f(1:end-1);0];
dfb=[0;f(1:end-1)-f(2:end)];
% driftmod=@(A1,A2,m,tau1,tau2,tdriftswitch,z,x) [A1*(1-exp(-x(x<=tdriftswitch)/tau1))+m*x(x<=tdriftswitch)+z;A1*(1-exp(-x(x>tdriftswitch)/tau1))+A2*(1-exp(-(x(x>tdriftswitch)-ton)/tau2))+m*x(x>tdriftswitch)+z];
%
% driftmod2=@(A1,A2,m1,m2,tau1,tau2,tdriftswitch,z,x) [A1*(1-exp(-x(x<=tdriftswitch)/tau1))+m1*x(x<=tdriftswitch)+z;A1*(1-exp(-x(x>tdriftswitch)/tau1))+A2*(1-exp(-(x(x>tdriftswitch)-tdriftswitch)/tau2))+m2*(x(x>tdriftswitch)-tdriftswitch)+m1*x(x>tdriftswitch)+z];
%
%
% driftdermod=@(A1,A2,m1,m2,tau1,tau2,tdriftswitch,x) [(A1/tau1)*(exp(-x(x<=tdriftswitch)/tau1))+m1;(A1/tau1)*(exp(-x(x>tdriftswitch)/tau1))+(A2/tau2)*(exp(-(x(x>tdriftswitch)-tdriftswitch)/tau2))+m2+m1];
%
actfittype=fittype('activationModelDrift8(A,dact,mact,nact,rho,ton,zA1,zA2,zm1,zm2,ztau1,ztau2,ztdriftswitch,zz,x)');
%put some bounds on the fitting based on the fit
%for the initial drift and some data features
mind=1/double(indmax-indactmin);
[fmin2,imin2]=min(fu(indactmin:indmax,1));
amp=(fmax-fmin2);
amp=max(f(1:indmax)-driftfit(t(1:indmax)));
% estimate some good initial guesses based on the data
indhalf=find(fact(tact>t(indmin))-fmin>=0.5*(fmax-fmin),1)+indmin;
ton0=(0.25*t(indactmin)+0.75*t(ipmax2));
ton0=t(indactmin);
drift1=driftmod2(driftfit.A1,0,driftfit.m1,0,driftfit.tau1,Inf,driftfit.tdriftswitch,driftfit.z,t);
drift1p=driftdermod(driftfit.A1,0,driftfit.m1,0,driftfit.tau1,Inf,driftfit.tdriftswitch,t);
amp=max([fu(indactmin,1);fu(indactmin:indmax,1)]-[drift1(indactmin);drift1(indactmin:indmax)]);
if amp<0
out=[];
return;
end
id0=find(([fu(indactmin,1);fu(indactmin:indmax-1,1)]-[drift1(indactmin);drift1(indactmin:indmax-1)])<0.5*amp&(fu(indactmin:indmax,1)-drift1(indactmin:indmax))>=0.5*amp)+double(indactmin)-1;
d0=t(id0);
d0=mean(d0-ton0)/(tmax-ton0);
% xconv=find(yp(indactmin:ipmax2)-yp((indactmin:ipmax2)-1)<0,1)+indactmin-1;
% n0=-0.5/log(((t(xconv)-t(indactmin))/(tmax-ton0))/d0);
% m0=yp(find(t==tmax,1)-1)/(length(t)*dt);
im0=find(fu(1:indmax,2)>0,1,'last');
m0=yp(im0)/(length(t)*dt);
% fphalf=fu(id0,2)/(length(t)*dt);
fphalf=max(fu(indactmin:indmax,2)/(length(t)*dt));
n0=4*(fphalf-drift1p(id0)-m0/2)*d0*(tmax-ton0);
try
if n0>maxn/2||n0<0
disp(n0)
end
catch e
display('problem ~577')
getReport(e);
end
xact=(ton0:dt:tmax)-ton0;
dact0=d0*(xact(end));
hillact=(xact.^n0)./((xact.^n0)+((dact0)^n0));
a0=amp-m0*trapz(hillact,xact);
lact=[max(a0/2,amp/2),mind,0,n0/2,0,0,ld];
uact=[Inf,1-mind,maxm*10,maxn,1,t(ipmax2),ud];
A0=amp;
iact=find(t>=ton0,1);
xact=t(iact:indmax)-t(iact);
hillact=(xact.^n0)./((xact.^n0)+((dact0)^n0));
idact0=find(t>ton0+d0,1)-iact;
idact0=max(idact0,1);
Hillpact0=m0*hillact+n0*A0*(xact.^(n0-1))*(d0^n0)./(((xact.^n0)+d0^n0).^2);
try
uu=Hillpact0(idact0:end)-fu(iact+idact0-1:indmax,2)/(length(t)*dt)+drift1p(iact+idact0-1:indmax);
catch e
display('problem ~607')
getReport(e)
end
uu=abs(uu)+abs([uu(1);uu(1:end-1)])+abs([uu(2);uu(2:end)]);
uu=uu/3;
% cf(); plot(exp(-uu));
[~,muu]=min(uu);
rho0=1-(muu+idact0-1)/((indmax-iact+1));
sact=[amp,d0,m0,n0,rho0,ton0,df.A1,df.A2,df.m1,df.m2,df.tau1,df.tau2,tmax+(t(end)-tmax)/double(2),df.z];
snr=((max(f)-min(f))/noise);
%fit the data
if length(tact)>=8
fitting=1;
tsignalact=tact;
signalact=fact;
try
w=ones(size(tact2));
w(1:indactminclean)=d(1:indactminclean);
w(1:indactminclean)=w(1:indactminclean)./(sum(w(1:indactminclean))/double(indactminclean));
w(length(tact2)-(length(d)-indactminclean-1):end)=d(indactminclean+1:end);
w(length(tact2)-(length(d)-indactminclean-1):end)=w(length(tact2)-(length(d)-indactminclean-1):end)./(sum(w(length(tact2)-(length(d)-indactminclean-1):end))/double((length(d)-indactminclean-1)));
dadj=sum(w)*dadj/sum(dadj);
wint=abs(fmin2+amp-fu(end,1))/abs(fmin2-fu(end,1));
actfit=fit([tact2;tact2dirty;tdrift;tdrift;tact2],[fact2;ypact;fdrift;ypdrift;zeros(size(tact2))],actfittype,'Lower',lact,'Upper',uact,'StartPoint',sact,'Weight',[snr*snr*w;snr*wyp;dadj;dadj;wint*mean(w)*ones(size(tact2))],'Robust','Bisquare','Display','off','Algorithm','Trust-Region');
catch e
display('problem ~644')
disp('error in activation fit')
end
% if ~isempty(regexp(lastwarn,'starting'))
% disp(lastwarn)
% end
signal=f(~spike);
fitting=0;
%amplitube of the response
% out.amplitude=actfit(tact(end))-actfit(actfit.ton);
%time of onset of response
% indon= find(t-actfit.ton<0,1,'last');
indon=indactmin;
sigma=mean(abs(fu(~spike,1)-f(~spike)));
% if fu(indon+1)-fu(indon)>4*sigma
% out.ton=indon;
% else
actsol=actfit(t);
out.amplitude=actsol(find(t>=tact(end),1))-actsol(find(t<=actfit.ton,1,'last'));
if ~isempty(plt) && plt
figure(1);
% subplot(2,1,1);
hold on
h=plot(t,actsol+offset,'LineStyle','-','Color',[1 0.5 0]);
hlabel=[hlabel; h];
set(h,'linewidth',2)
hleg=legend(hlabel,'Data','Noise Spike','Estimated Drift','Estimated Activation','TV Data Estimate','Initial Drift Fitting','Activation Fitting','Location','NorthWest');
hh=findall(gca,'DisplayName','Initial Drift Fitting');
if ~isempty(hh)
set(hh,'LineStyle',':')
end
cornerLegend(hleg);
ylim([min(f),max(f)]+offset);
annotateActivation();
hold off
end
if abs(actsol(end)-fu(end,1))>0.2*amp
disp('out in the boonies')
end
% if plt
% figure(1);
% clf(1);
% hold on
% plot(actfit,tact,fact);
% x=x_to_norm(actfit.ton,actfit.ton);
% ton=actfit.ton;
% y=y_to_norm(0.5*fmax,actfit(ton));
% annotation('textarrow',x,y,'String',['t_{on} = ' num2str(actfit.ton) ' s'])
% hold off
% end
fitting=1;
respfittype=fittype('responseModelDrift11(Aoff,Aon,dact,dde,mact,nact,nde,rhoact,rhode,tdecay,ton,zA1,zA2,zm1,zm2,ztau1,ztau2,ztdriftswitch,zz,x)');
% driftmod2=@(ton,A1,A2,m1,m2,tau1,tau2,z,x) [A1*(1-exp(-x(x<=ton)/tau1))+m1*x(x<=ton)+z;A1*(1-exp(-x(x>ton)/tau1))+A2*(1-exp(-(x(x>ton)-ton)/tau2))+m2*(x(x>ton)-ton)+m1*x(x>ton)+z];
fitting=0;
%find the indices where the fluorescence crosses the half max
actdrift1=driftmod2(actfit.zA1,0,actfit.zm1,0,actfit.ztau1,Inf,actfit.ztdriftswitch,actfit.zz,t);
actdrift1p=driftdermod(actfit.zA1,0,actfit.zm1,0,actfit.ztau1,Inf,actfit.ztdriftswitch,t);
actdrift10=actdrift1;
if sum(abs(actdrift1-fu(:,1)))<sum(abs(drift1-fu(:,1))) || sum(abs(actdrift1-fu(:,1)))<sum(abs(driftsol-fu(:,1)))
if sum(abs(drift1-fu(:,1)))<sum(abs(driftsol-fu(:,1)))
actdrift1=drift1;
actdrift1p=drift1p;
zA10=driftfit.A1;
zm10=driftfit.m1;
ztau10=driftfit.tau1;
ztdriftswitch0=driftfit.tdriftswitch;
zz0=driftfit.z;
else
actdrift1=driftmod2(df.A1,0,df.m1,0,df.tau1,Inf,df.tdriftswitch,df.z,t);
actdrift1p=driftdermod(df.A1,0,df.m1,0,df.tau1,Inf,df.tdriftswitch,t);
zA10=df.A1;
zm10=df.m1;
ztau10=df.tau1;
ztdriftswitch0=df.tdriftswitch;
zz0=df.z;
end
else
zA10=actfit.zA1;
zm10=actfit.zm1;
ztau10=actfit.ztau1;
ztdriftswitch0=actfit.ztdriftswitch;
zz0=actfit.zz;
end
mact0=actfit.mact;
nact0=actfit.nact;
Aon0=actfit.A;
% Hillpact0=mact0*hillact+nact0*Aon0*(xact.^(nact0-1))*(dact0^nact0)./(((xact.^nact0)+dact0^nact0).^2);
%
% try
% uu=Hillpact0(idact0:end)-fu(iact+idact0-1:indmax,2)/(length(t)*dt)+actdrift1p(iact+idact0-1:indmax);
% catch e
% getReport(e)
% end
% uu=abs(uu)+abs([uu(1);uu(1:end-1)])+abs([uu(2);uu(2:end)]);
% uu=uu/3;
% % cf(); plot(exp(-uu));
% [~,muu]=min(uu);
dact0=d0*(xact(end));
tact=(actfit.ton:dt:tmax);
if length(tact)==1
tact=[actfit.ton tmax];
end
xact=tact-actfit.ton;
dact0=d0*(xact(end));
hillact=(xact.^n0)./((xact.^n0)+((dact0)^n0));
rhoact0=actfit.rho;
try
A0=Aon0*hillact(end)+mact0*trapz(xact,hillact);
catch e
getReport(e)
end
A00=A0;
fsmooth=fu(:,1);
[fmin2,imin2]=min(fu(indactmin:indmax,1));
imin2=imin2+indactmin-1;
amp=(fmax-fmin2);
endcross=find(fsmooth(indmax:end)<=actdrift1(indmax:end),1)+indmax-1;
subdrift1=true;
if isempty(endcross)||endcross==indmax
% endcross=length(t);
[~,endcross]=min(fsmooth(indmax:end));
endcross=endcross+indmax-1;
dsmooth=fsmooth(indmax:endcross);
delta=fsmooth-min(dsmooth);
ampcross=dsmooth(1);max(delta(indmax:endcross))-min(delta(indmax:endcross));
subdrift1=false;
else
dsmooth=fsmooth(indmax:endcross)-actdrift1(indmax:endcross);
ampcross=dsmooth(1);
delta=fsmooth-actdrift1-min(dsmooth);
end
indcrosshalf=[delta(indmax); delta(indmax:end-1)]>A0/2&delta(indmax:end)<=A0/2;
indcrosshalf=find(indcrosshalf,1)+indmax-1;
thalf=mean(t(indcrosshalf));
%
% indcrossquarter=[f(1); f(1:end-1)]>0.75*fmax&[t(1); t(1:end-1)]>tmax&f<=0.75*fmax&t>tmax&[~spike(1);~spike(1:end-1)];
% indcrossquarter(spike)=0;
% tquarter=mean(t(indcrossquarter));
if isnan(thalf)
disp('Could not detect deactivation.')
return;
end
[~, idx] = min(abs(t-actfit.ton)); %index of closest value
hillup=@(x,n,beta) (x^n)/((x^n)+(beta^n));
hilldown=@(x,n,beta) (beta^n)/((x^n)+(beta^n));
hillpdown=@(x,n,beta) -(n*(beta^n)*(x^(n-1)))/(((x^n)+(beta^n))^2);
tdact=actfit.dact*(tmax-actfit.ton)+actfit.ton;
rhoact0=max(3/(indmax-find(t<=tdact,1,'last')),0.5);
% rhode0=max(-3/(indmax-find(t<=thalf,1,'last')),0.5);
hillend=hillup((tmax-actfit.ton),actfit.nact,actfit.dact*(tmax-actfit.ton));
mde0=max(yp(find(t==tmax,1)+1)/(length(t)*dt),-maxm);
% mde0=0;
dde0=(thalf-tmax)/(tend-tmax);
[fmin3,imin3]=min(fu(indmax:end,1));
imin3=imin3+indmax-1;
ddrift=actdrift1(imin3)-actdrift1(imin2);
Aoff0=(actfit.A*hillend+actfit.mact*(tmax-tdact)-(fmin3-fmin2)+mde0*(thalf-tmax))+ddrift;
% hillend2=Aoff0*hillup(t(end)-tmax,nde0,dde0*(thalf-tmax));
% hillpend2=Aoff0*hillpdown((t(end)-tmax),nde0,dde0*(thalf-tmax));
% this is really excessive we need to take into accoubt drift 1 and
% the exponential component of drift 2 otherwise the initial geuss is
% overcompensating
ztau20=t(end)-tmax;
%
% iact=find(t>=actfit.ton,1);
% xact=t(iact:indmax)-t(iact);
% nact=actfit.nact;
% hillact=(xact.^nact)./((xact.^nact)+((actfit.dact*(xact(end)))^nact));
% dact0=actfit.dact*(xact(end));
% idact0=find(t>actfit.ton+dact0,1)-iact;
% idact0=max(idact0,1);
nde0=4;
% indcrosshalf=find(indcrosshalf,1)+indmax-1;
nn=1;
beta0=dde0*(tend-tmax);
xde=t(indmax:end)-t(indmax);
hillde=1-(xde.^nde0)./((xde.^nde0)+(beta0^nde0));
intlinde=trapz(xde,hillde);
%ensures linear portion is less than half
mde0=max(-A0/(2*intlinde),mde0);
[fphalf,iphalf]=min(fu(indmax:endcross,2)/(length(t)*dt));
fpphalf=(fu(indmax:end,2)-[fu(indmax,2); fu(indmax:end-1,2)])/((length(t)*dt^2));
fpphalf=fpphalf(indcrosshalf-indmax+1);
% fphalf=min(fphalf,-A/4);
Aoff0=max(0,(A0+intlinde*mde0)/((1-hillde(end))*A0));
nmin0=sqrt(2);
bd=(thalf-tmax);
while nn<6
if subdrift1
nde0=-(fphalf-mde0/2-actdrift1p(indcrosshalf))*4*bd/(Aoff0*A0);
nde2=(fpphalf-(actdrift1p(indcrosshalf)-actdrift1p(indcrosshalf-1))/dt)/(mde0/(4*bd)+Aoff0*A0/(4*bd^2));
else
nde0=-(fphalf-mde0/2)*4*(thalf-tmax)/(Aoff0*A0);
nde2=(fpphalf)/(mde0/(4*bd)+Aoff0*A0/(4*bd^2));
end
nde2=max(nde2,1.01);
nde2=min(nde2,maxn/sqrt(2));
nde0=min(nde0,maxn/sqrt(2));
nde0=max(nde0,nmin0);
nde0=min(nde2,nde0);
hillde=1-(xde.^nde0)./((xde.^nde0)+(beta0^nde0));
intlinde=trapz(xde,hillde);
mde0=max(-A0/(2*intlinde),mde0);
Aoff0=max(0,(A0+intlinde*mde0)/((1-hillde(end))*A0));
% Aoff0=min(Aoff0,1);
intlindehalf=trapz(xde(xde<beta0),hillde(xde<beta0));
Delta=max(A0-(fu(indcrosshalf,1)-actdrift1(indcrosshalf)),0);
mde0=-(Delta-Aoff0*A0*(hillde(find(xde>=beta0,1))))/intlindehalf;
mde0=min(mde0,0);
% A0=((fu(indcrosshalf,1)-actdrift1(indcrosshalf))-Aoff0*A0*hillde(find(xde>=beta0,1))-mde0*intlindehalf)
% r0=r0/A0;
nn=nn+1;
end
mde0=-A0*(1-Aoff0*(1-hillde(end)))/intlinde;
tf=t(end)-ztdriftswitch0;
c=A0-Aoff0*A0;
xde=t(indmax:end)-t(indmax);
beta0=(dde0*(t(end)-tmax));
hillde=(1-(xde.^nde0)./((xde.^nde0)+(beta0.^nde0)));
hillendde=hillde(end);
delta2=Aoff0*A0*hillendde...
+mde0*trapz(xde,1-((xde.^nde0)./((xde.^nde0)+(beta0^nde0))))...
+c;
df=mean(fu(end-1:end,1))-(actdrift1(end)+delta2);
driftfinal=df;
jj=find(d(1:end-1)>[d(1);d(1:end-2)],1,'last');
driftpfinal=sum(d(jj:end).*fu(end-length(d)+jj:end,2)/(length(t)*dt))/sum(d(jj:end));
driftpfinal=mean(fu(inddrift:end,2)/(length(t)*dt));
Hillpde0=mde0*hillde-nde0*Aoff0*A0*(xde.^(nde0-1))*(beta0^nde0)./(((xde.^nde0)+beta0^nde0).^2);
driftpfinal=driftpfinal-actdrift1p(end)-Hillpde0(end);
%%also need to subtract drift contributions to derivative
uu=Hillpde0(1:indcrosshalf-indmax+1)-fu(indmax:indcrosshalf,2)/(length(t)*dt)+actdrift1p(indmax:indcrosshalf);
uu=abs(uu)+abs([uu(1);uu(1:end-1)])+abs([uu(2);uu(2:end)]);
uu=uu/3;
% cf(); plot(exp(-uu));
[~,muu]=min(uu);
rhode0=muu/(find(t==tend,1)-indmax+1);
jj=max(find(t>ztdriftswitch0,1));
if isempty(jj)|| jj>=indmax
else
jj=length(f)-1;
end