removed old matlab code from repo

DR_oldmatlabcode/DFAsj_getthetacrosscov_timecondition4.m → DFAnalysis/DFAsj_getthetacrosscov_timecondition4.m

@@ -272,17 +272,17 @@
 
 
 % if (appendindex)
-%     out.index = ind;
+%     out.index = ind;  
 % end
 out.index = ind;
-out.T = T;
+out.T = T; 
 out.p1p2 = exp_p;
 out.corr = xc;
 out.rawcorr = rawcorr;
-out.Zcrosscov = Zcrosscov;
+out.Zcrosscov = Zcrosscov; %% i think used to calc stats? but also plotted
 out.crosscov = crosscov;
 out.rawcorr_sm = rawcorr_sm;
-out.Zcrosscov_sm = Zcrosscov_sm;
+out.Zcrosscov_sm = Zcrosscov_sm; %% USED to plot 
 out.crosscov_sm = crosscov_sm;
 out.Neventscorr = Neventscorr;
 

DFAnalysis/dfa_phaseXcorr.m

@@ -9,8 +9,12 @@
 %   'bin', n 	binsize in sec. Default 0.002 (2 ms)
 %   'tmax', n	maximum time for cross correlation. Default 1 sec.
 
-bin = .001; % s
-tmax = .5; % s
+bin = 0.01; % seconds
+sw1 = bin*3; % seconds
+sw2 = 0.250;
+rmstmax = 0.1;
+rmsmincounts = 50;
+tmax = 1;
 try assign(varargin{:}); catch; end
 
 % check for required data in varargin
@@ -21,7 +25,6 @@
     end
 end
 
-% fuck this won't work for pairs.. 
 day = idx(1);
 ntA = idx(2);
 clustA = idx(3);
@@ -30,6 +33,8 @@
 eps = idx(6:end);
 
 out = init_out();
+out.index = idx;
+
 % for each cell we calculate the cross correlation 
 t1 = [];
 t2 = [];
@@ -54,39 +59,69 @@
 %% get lickbout licks
 [intraBoutXP, ~] = getLickBoutLicks(animal, [repmat(day,length(eps),1) eps'], varargin);
 intraBoutXPvec = intraBoutXP{day}{eps};
-eventTimes = intraBoutXPvec(ismember(intraBoutXPvec, eventTimes));
+licks = cell2mat([arrayfun(@(x) lick{day}{x}.starttime, eps, 'un', 0)']);
+eventTimes = intraBoutXPvec(ismember(intraBoutXPvec, licks));
 
-numEventsPerEp = [];
-for e = 1:length(eps)
-    epStartTime = spikes{day}{eps(e)}{nt}{clust}.timerange(1);
-    epEndTime = spikes{day}{eps(e)}{nt}{clust}.timerange(2);
-    numEventsPerEp = [numEventsPerEp; sum(logical(isExcluded(eventTimes, [epStartTime epEndTime])))];
-end
+% numEventsPerEp = [];
+% for e = 1:length(eps)
+%     epStartTime = spikes{day}{eps(e)}{nt}{clust}.timerange(1);
+%     epEndTime = spikes{day}{eps(e)}{nt}{clust}.timerange(2);
+%     numEventsPerEp = [numEventsPerEp; sum(logical(isExcluded(eventTimes, [epStartTime epEndTime])))];
+% end
 
 %% transform spikes into a phase vector
 % how? each spike is a spike time.. i need each spike time relative to
 % preceeding lick then ratio to interlickinterval duration to get %.. then
 % radians.. then that + (2pi*[preceding lick number])
 
+% spiketrain A
+% ILI = diff(eventTimes); % diff gives duration from each lick to the next
+[~, ~, spikebin] = histcounts(t1cnd, eventTimes);
+spikesILImask = spikebin~=0;
+t1LB = t1cnd(spikesILImask);
+binTimeStart = eventTimes(spikebin(spikesILImask));
+binTimeEnd = eventTimes(spikebin(spikesILImask)+1);
+
+ILI = (binTimeEnd - binTimeStart);
+t1FromLick = (t1LB - binTimeStart);
+
+pctSpikeILI = t1FromLick./ILI;
+
+% for each valid ILI, increment its spikes to be pct of ILI + the ILI index
+t1SpikePctILIbin = spikebin(spikesILImask)+pctSpikeILI;
+
+% spiketrain B
+[~, ~, spikebin] = histcounts(t2cnd, eventTimes);
+spikesILImask = spikebin~=0;
+t2LB = t2cnd(spikesILImask);
+binTimeStart = eventTimes(spikebin(spikesILImask));
+binTimeEnd = eventTimes(spikebin(spikesILImask)+1);
 
+ILI = (binTimeEnd - binTimeStart);
+t2FromLick = (t2LB - binTimeStart);
+
+pctSpikeILI = t2FromLick./ILI;
+
+% for each valid ILI, increment its spikes to be pct of ILI + the ILI index
+t2SpikePctILIbin = spikebin(spikesILImask)+pctSpikeILI;
 
 %% run phase xcorr
 
 % get xc
-xc = spikexcorr(t1cnd,t2cnd, bin, tmax);
+xc = spikexcorr(t1SpikePctILIbin,t2SpikePctILIbin, bin, tmax);
 % normalize
 normxc = xc.c1vsc2 ./ sqrt(xc.nspikes1 * xc.nspikes2);
 % smooth
 try
     nstd=round(sw1/(xc.time(2) - xc.time(1)));
 catch
-    if xc.nspikes1 == 0
-        emptynt = index(3:4);
-    elseif xc.nspikes2 == 0
-        emptynt = index(5:6);
-    end
-    fprintf('no spikes %d %d %d %d\n', day, epoch, emptynt(1),emptynt(2))
-    out = make_blank(index);
+%     if xc.nspikes1 == 0
+%         emptynt = index(3:4);
+%     elseif xc.nspikes2 == 0
+%         emptynt = index(5:6);
+%     end
+    fprintf('missing spikes \n') %d %d %d %d %d %d\n', day, epoch, emptynt(1),emptynt(2))
+%     out = make_blank(index);
     return
 end
 g1 = gaussian(nstd, 2*nstd+1);
@@ -95,35 +130,36 @@
 % bins = find(abs(xc.time)<=0.2);
 %     Neventscorr = sum(xc.c1vsc2(bins));
 % Expected probability
-p1 = xc.nspikes1/T;
-p2 = xc.nspikes2/T; % fr in Hz
-expProb = p1*p2; % per sec
-
+% p1 = xc.nspikes1/T;
+% p2 = xc.nspikes2/T; % fr in Hz
+% expProb = p1*p2; % per sec
 
 % compute the excess correlation at 0 lag
 exc = excesscorr(xc.time, xc.c1vsc2, xc.nspikes1, xc.nspikes2, sw1, sw2);
 % compute RMS
 xcrms = xcorrrms(xc.time, xc.c1vsc2, rmstmax, rmsmincounts);
+
 % output
-out.index = index;
+out.bin = bin;
+out.tmax = tmax;
 % out.T = T;
 out.xc = xc;
 out.normxc = normxc;
 out.smthxc = smthxc;
-out.expProb = expProb;
+% out.expProb = expProb;
 % out.xcShfmean = xcShfmean;
 % out.xcShfLag0 = xcShfLag0;
 out.excesscorr = nanmean(exc); % nanmean in case there are two bins equally near lag zero
 out.xcrms = xcrms;
 end
 
 function out = init_out()
-out.tmax = [];
-out.bin = [];
-out.xc = [];
-out.normxc = [];
-out.smthxc = [];
-out.expProb = [];
-out.excesscorr = [];
-out.xcrms = [];
+out.tmax = nan;
+out.bin = nan;
+out.xc = nan;
+out.normxc = nan;
+out.smthxc = nan;
+% out.expProb = [];
+out.excesscorr = nan;
+out.xcrms = nan;
 end

DFFunctions/Iterators/iter_multiEpoch_multiCluster.m

@@ -66,7 +66,7 @@
             clustB = unqNtCell(c,4);
             eps = f(a).epochs{g}(deIdx,2)';
             cindex = [day ntA clustA ntB clustB eps];
-            fprintf('--%s %s day %d nt %d cl %d :: eps %s\n', f(a).function.name, ...
+            fprintf('--%s %s day %d nt-cl %d-%d x %d-%d :: eps %s\n', f(a).function.name, ...
                 f(a).animal{1}, day, ntA, clustA, ntB, clustB,...
                 strjoin(num2cell(num2str(eps(:)))',' '));
             % run the specified filter function on this day cell

DR_oldmatlabcode/DFSsj_HPexpt_ThetacorrAndRipresp_ver4.m → DFScripts/DFSsj_HPexpt_ThetacorrAndRipresp_ver4.m

@@ -416,7 +416,7 @@
         all_trialResps1_epcomb=[]; all_trialResps2_epcomb=[]; all_trialResps1rdm_epcomb=[]; all_trialResps2rdm_epcomb=[];
         r=[]; p=[]; r_rdm=[]; p_rdm=[];
 
-        for r=ind
+        for r=inde
             % Theta Corr variables
             % --------------------
             allZcrosscov_sm_runtheta_epcomb = [allZcrosscov_sm_runtheta_epcomb; allZcrosscov_sm_runtheta(r,:)];
@@ -627,7 +627,7 @@
     line([0.1 0.1], [min(runthetaZ) max(runthetaZ)],'Color',[0.5 0.5 0.5],'LineWidth',1);
     line([-0.1 -0.1], [min(runthetaZ) max(runthetaZ)],'Color',[0.5 0.5 0.5],'LineWidth',1);
 
-    title(sprintf('Mean Std. CrossCov - Rip %s Cells',...
+    title(sprintf('Mean Cov - Rip %s Cells',...
         kind),'FontSize',20)
     set(gca,'XLim',[-0.4 0.4]);
     xlabel('Time (sec)','FontSize',20);