Tf.win = dftfilt(winsize,maxfreq/srate,cycles,padratio,cyclesfact);   Tf.nb_points = size(Tf.win,2);end;Tf.tmpalltimes = zeros(Tf.nb_points, timesout);trials = length(X)/frame;if saveall   Tf.tmpall     = repmat(nan,[trials timesout Tf.nb_points]);else   Tf.tmpall = [];endTf.tmpallbool = zeros(trials,timesout);Tf.ITCdone = 0;if Tf.subitc   Tf.ITC  = zeros(Tf.nb_points, timesout);   switch Tf.type,	   case { 'coher' 'phasecoher2' }		Tf.ITCcumul  = zeros(Tf.nb_points, timesout);   end;end;% function for itc% ----------------function [Tf, itcvals] = tfitc(Tf, trials, times);Tf = tfcomp(Tf, trials, times);switch Tf.type   case 'coher',      Tf.ITC(:,times)      = Tf.ITC(:,times) + Tf.tmpalltimes; % complex coher.      Tf.ITCcumul(:,times) = Tf.ITCcumul(:,times)+abs(Tf.tmpalltimes).^2;   case 'phasecoher2',      Tf.ITC(:,times)      = Tf.ITC(:,times) + Tf.tmpalltimes; % complex coher.      Tf.ITCcumul(:,times) = Tf.ITCcumul(:,times)+abs(Tf.tmpalltimes);   case 'phasecoher',      Tf.ITC(:,times)      = Tf.ITC(:,times) + Tf.tmpalltimes ./ abs(Tf.tmpalltimes);                                                             % complex coher.end % ~any(isnan())return;function [Tf, itcvals] = tfitcpost(Tf, trials);switch Tf.type   case 'coher',       Tf.ITC = Tf.ITC ./ sqrt(trials * Tf.ITCcumul);   case 'phasecoher2', Tf.ITC = Tf.ITC ./ Tf.ITCcumul;   case 'phasecoher',  Tf.ITC = Tf.ITC / trials; % complex coher.end % ~any(isnan())if Tf.saveall  Tf.ITC = transpose(Tf.ITC); % do not use ' otherwise conjugate	%imagesc(abs(Tf.ITC)); colorbar; figure;	%squeeze(Tf.tmpall(1,1,1:Tf.nb_points))	%squeeze(Tf.ITC   (1,1,1:Tf.nb_points))	%Tf.ITC = shiftdim(Tf.ITC, -1);	Tf.ITC = repmat(shiftdim(Tf.ITC, -1), [trials 1 1]);	Tf.tmpall = (Tf.tmpall - abs(Tf.tmpall) .* Tf.ITC) ./ abs(Tf.tmpall);  %	for index = 1:trials  %		imagesc(squeeze(abs(Tf.tmpall(index,:,:)))); drawnow; figure;  %		Tf.tmpall(index,:,:) = (Tf.tmpall(index,:,:) - Tf.tmpall(index,:,:) .* Tf.ITC)./Tf.tmpall(index,:,:);  %		imagesc(squeeze(abs(Tf.tmpall(index,:,:)))); drawnow;  %		subplot(10,10, index); imagesc(squeeze(abs(Tf.tmpall(index,:,:)))); caxis([0 1]); drawnow;  %	end;  %	squeeze(Tf.tmpall(1,1,1:Tf.nb_points))  %	figure; axcopy;end;Tf.ITCdone = 1;return;% function for time freq decomposition% ------------------------------------function [Tf, tmpX] = tfcomp(Tf, trials, times);% tf is an structure containing all the information about the decompositionfor trial = trials   for index = times      if ~Tf.tmpallbool(trial, index) % already computed         tmpX = Tf.X([1:Tf.winsize]+floor((index-1)*Tf.stp)+(trial-1)*Tf.frame);                  if ~any(isnan(tmpX)) % perform the decomposition            tmpX = tmpX - mean(tmpX);            switch Tf.detret, case 'on',                tmpX = detrend(tmpX);             end;                        if Tf.cycles == 0 % use FFTs               tmpX = Tf.win .* tmpX(:);               tmpX = fft(tmpX,Tf.padratio*Tf.winsize);               tmpX = tmpX(2:Tf.padratio*Tf.winsize/2+1);            else                tmpX = transpose(Tf.win) * tmpX(:);            end         else            tmpX = NaN;         end;         if Tf.ITCdone            tmpX = (tmpX - abs(tmpX) .* Tf.ITC(:,index)) ./ abs(tmpX);         end;         Tf.tmpalltimes(:,index) = tmpX;         if Tf.saveall            Tf.tmpall(trial, index,:) = tmpX;            Tf.tmpallbool(trial, index) = 1;         end	  else		  Tf.tmpalltimes(:,index) = Tf.tmpall(trial, index,:);     end;   end;end;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%    COHERENCE    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function for coherence initialisation% -------------------------------------function Coher = coherinit(nb_points, trials, timesout, type);Coher.R  = zeros(nb_points,timesout);       % mean coherence% Coher.RR = repmat(nan,nb_points,timesout); % initialize with nansCoher.type = type;Coher.Rn=zeros(trials,timesout);switch type case 'coher',  Coher.cumulX = zeros(nb_points,timesout);  Coher.cumulY = zeros(nb_points,timesout); case 'phasecoher2',  Coher.cumul  = zeros(nb_points,timesout);end;% function for coherence calculation% -------------------------------------% function Coher = cohercomparray(Coher, tmpX, tmpY, trial);% switch Coher.type%   case 'coher',%      Coher.R = Coher.R + tmpX.*conj(tmpY); % complex coher.%      Coher.cumulXY = Coher.cumulXY + abs(tmpX).*abs(tmpY);%   case 'phasecoher',%      Coher.R = Coher.R + tmpX.*conj(tmpY) ./ (abs(tmpX).*abs(tmpY)); % complex coher.%      Coher.Rn(trial,:) = 1;% end % ~any(isnan())function [Coher,tmptrialcoh] = cohercomp(Coher, tmpX, tmpY, trial, time);tmptrialcoh = tmpX.*conj(tmpY);switch Coher.type   case 'coher',      Coher.R(:,time) = Coher.R(:,time) + tmptrialcoh; % complex coher.      Coher.cumulX(:,time) = Coher.cumulX(:,time) + abs(tmpX).^2;      Coher.cumulY(:,time) = Coher.cumulY(:,time) + abs(tmpY).^2; case 'phasecoher2',      Coher.R(:,time) = Coher.R(:,time) + tmptrialcoh; % complex coher.      Coher.cumul(:,time) = Coher.cumul(:,time) + abs(tmptrialcoh);   case 'phasecoher',      Coher.R(:,time) = Coher.R(:,time) + tmptrialcoh ./ abs(tmptrialcoh); % complex coher.	  %figure; imagesc(abs(tmpX.*conj(tmpY) ./ (abs(tmpX).*abs(tmpY))));      Coher.Rn(trial,time) = Coher.Rn(trial,time)+1;end % ~any(isnan())% function for post coherence calculation% ---------------------------------------function Coher = cohercomppost(Coher, trials);switch Coher.type case 'coher',   Coher.R = Coher.R ./ sqrt(Coher.cumulX) ./ sqrt(Coher.cumulY); case 'phasecoher2',   Coher.R = Coher.R ./ Coher.cumul; case 'phasecoher',   Coher.Rn = sum(Coher.Rn, 1);   Coher.R  = Coher.R ./ (ones(size(Coher.R,1),1)*Coher.Rn); % coherence magnitudeend;% function for 2 conditions coherence calculation% -----------------------------------------------function [coherimage, coherimage1, coherimage2] = coher2conddiff( allsavedcoher, alltrials, cond1trials, type, tfx, tfy);	t1s = alltrials(1:cond1trials);	t2s = alltrials(cond1trials+1:end);	switch type	 case 'coher',	  coherimage1 = sum(allsavedcoher(:,:,t1s),3) ./ sqrt(sum(tfx(:,:,t1s),3)) ./ sqrt(sum(tfy(:,:,t1s),3));	  coherimage2 = sum(allsavedcoher(:,:,t2s),3) ./ sqrt(sum(tfx(:,:,t2s),3)) ./ sqrt(sum(tfy(:,:,t1s),3));	 case 'phasecoher2',	  coherimage1 = sum(allsavedcoher(:,:,t1s),3) ./ sum(abs(allsavedcoher(:,:,t1s)),3);	  coherimage2 = sum(allsavedcoher(:,:,t2s),3) ./ sum(abs(allsavedcoher(:,:,t2s)),3);	 case 'phasecoher',	  coherimage1 = sum(allsavedcoher(:,:,t1s),3) / cond1trials;	  coherimage2 = sum(allsavedcoher(:,:,t2s),3) / (size(allsavedcoher,3)-cond1trials);	end;	coherimage = coherimage2 - coherimage1;	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% BOOTSTRAP %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function for bootstrap initialisation% -------------------------------------function Boot = bootinit(Coherboot, nb_points, timesout, naccu, baselength, baseboot, boottype, alpha, rboot);Boot.Rboot       = zeros(nb_points,naccu);  % summed bootstrap coherBoot.boottype    = boottype;Boot.baselength  = baselength;Boot.baseboot    = baseboot;Boot.Coherboot   = Coherboot;Boot.naccu       = naccu;Boot.alpha       = alpha;Boot.rboot       = rboot;% function for bootstrap computation% ----------------------------------function Boot = bootcomp(Boot, Rn, tmpalltimesx, tmpalltimesy);if ~isnan(Boot.alpha) & isnan(Boot.rboot)   if strcmp(Boot.boottype, 'times') % get g.naccu bootstrap estimates for each trial      goodbasewins = find(Rn==1);      if Boot.baseboot % use baseline windows only         goodbasewins = find(goodbasewins<=Boot.baselength);       end      ngdbasewins = length(goodbasewins);      j=1;      tmpsX = zeros(size(tmpalltimesx,1), Boot.naccu);      tmpsY = zeros(size(tmpalltimesx,1), Boot.naccu);      if ngdbasewins > 1         while j<=Boot.naccu            s = ceil(rand([1 2])*ngdbasewins); % random ints [1,g.timesout]            s = goodbasewins(s);            if ~any(isnan(tmpalltimesx(:,s(1)))) & ~any(isnan(tmpalltimesy(:,s(2))))               tmpsX(:,j) = tmpalltimesx(:,s(1));               tmpsY(:,j) = tmpalltimesy(:,s(2));               j = j+1;            end         end         Boot.Coherboot = cohercomp(Boot.Coherboot, tmpsX, tmpsY, 1, 1:Boot.naccu);      end;   endend;% handle other trial bootstrap types% ----------------------------------function [Boot, Rbootout] = bootcomppost(Boot, allRn, alltmpsX, alltmpsY);trials    = size(alltmpsX, 1);times     = size(alltmpsX, 2);nb_points = size(alltmpsX, 3);if ~isnan(Boot.alpha) & isnan(Boot.rboot)   if strcmp(Boot.boottype, 'trials') % get g.naccu bootstrap estimates for each trial      fprintf('\nProcessing trial bootstrap (of %d):',times(end));      tmpsX = zeros(size(alltmpsX,3), Boot.naccu);      tmpsY = zeros(size(alltmpsY,3), Boot.naccu );      Boot.fullcoherboot = zeros(nb_points, Boot.naccu, times);            for index=1:times         if rem(index,10) == 0,  fprintf(' %d',index); end         if rem(index,120) == 0, fprintf('\n'); end         for allt=1:trials            j=1;            while j<=Boot.naccu               t = ceil(rand([1 2])*trials); % random ints [1,g.timesout]               if (allRn(t(1),index) == 1) & (allRn(t(2),index) == 1)                  tmpsX(:,j) = squeeze(alltmpsX(t(1),index,:));                  tmpsY(:,j) = squeeze(alltmpsY(t(2),index,:));                  j = j+1;               end            end            Boot.Coherboot = cohercomp(Boot.Coherboot, tmpsX, tmpsY, 1, 1:Boot.naccu);         end;         Boot.Coherboot = cohercomppost(Boot.Coherboot);  % CHECK IF NECSSARY FOR ALL BOOT TYPE         Boot.fullcoherboot(:,:,index) = Boot.Coherboot.R;          Boot.Coherboot = coherinit(nb_points, trials, Boot.naccu, Boot.Coherboot.type);      end;      Boot.Coherboot.R = Boot.fullcoherboot;      Boot = rmfield(Boot, 'fullcoherboot');   elseif strcmp(Boot.boottype, 'timestrials') % handle timestrials bootstrap      fprintf('\nProcessing time and trial bootstrap (of %d):',trials);      tmpsX = zeros(size(alltmpsX,3), Boot.naccu);      tmpsY = zeros(size(alltmpsY,3), Boot.naccu );      for allt=1:trials         if rem(allt,10) == 0,  fprintf(' %d',allt); end         if rem(allt,120) == 0, fprintf('\n'); end         j=1;         while j<=Boot.naccu            t = ceil(rand([1 2])*trials); % random ints [1,g.timesout]            goodbasewins = find((allRn(t(1),:) & allRn(t(2),:)) ==1);            if Boot.baseboot % use baseline windows only               goodbasewins = find(goodbasewins<=baselength);             end            ngdbasewins = length(goodbasewins);                        if ngdbasewins>1               s = ceil(rand([1 2])*ngdbasewins); % random ints [1,g.timesout]               s=goodbasewins(s);                              if all(allRn(t(1),s(1)) == 1) & all(allRn(t(2),s(2)) == 1)                  tmpsX(:,j) = squeeze(alltmpsX(t(1),s(1),:));                  tmpsY(:,j) = squeeze(alltmpsY(t(2),s(2),:));                  j = j+1;               end            end         end         Boot.Coherboot = cohercomp(Boot.Coherboot, tmpsX, tmpsY, 1, 1:Boot.naccu);      end      Boot.Coherboot = cohercomppost(Boot.Coherboot);   elseif strcmp(Boot.boottype, 'times') % boottype is 'times'      Boot.Coherboot = cohercomppost(Boot.Coherboot);   end;end;% test if precomputedif ~isnan(Boot.alpha) & isnan(Boot.rboot) % if bootstrap analysis included . . .   % 'boottype'='times' or 'timestrials', size(R)=nb_points*naccu   % 'boottype'='trials',                 size(R)=nb_points*naccu*times   Boot.Coherboot.R = abs (Boot.Coherboot.R);   Boot.Coherboot.R = sort(Boot.Coherboot.R,2);   % compute bootstrap significance level   i = round(Boot.naccu*Boot.alpha);   Boot.Rsignif = mean(Boot.Coherboot.R(:,Boot.naccu-i+1:Boot.naccu),2); % significance levels for Rraw   Boot.Coherboot.R = squeeze(mean(Boot.Coherboot.R(:,Boot.naccu-i+1:Boot.naccu),2));   if size(Boot.Coherboot.R, 2) == 1	   Rbootout(:,2) = Boot.Coherboot.R;   else	   Rbootout(:,:,2) = Boot.Coherboot.R;   end;   % BEFORE   %Rboot = [mean(Rboot(1:i,:)) ; mean(Rboot(g.naccu-i+1:g.naccu,:))];elseif ~isnan(Boot.rboot)	Boot.Coherboot.R = Boot.rboot;	Boot.Rsignif     = Boot.rboot	Rbootout         = Boot.rboot;else 	Boot.Coherboot.R = [];	Boot.Rsignif     = [];	Rbootout         = [];end % NOTE: above, mean ?????function w = hanning(n)if ~rem(n,2)   w = .5*(1 - cos(2*pi*(1:n/2)'/(n+1)));   w = [w; w(end:-1:1)];else   w = .5*(1 - cos(2*pi*(1:(n+1)/2)'/(n+1)));   w = [w; w(end-1:-1:1)];end