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Fig3_rastersModelComparison.m
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Fig3_rastersModelComparison.m
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folder = 'G:\DATA\';
aavDatasets = {...
'2014-08-02_2023_MK012_TMwExtras.mat'; ...
'2014-08-04_1827_MK012_TMwExtras.mat'; ...
'2014-08-05_2228_MK012_TMwExtras.mat'; ...
'2014-08-08_2251_MK012_TMwExtras.mat'; ...
'2014-08-11_2133_MK012_TMwExtras.mat'; ...
'2014-08-13_2023_MK012_TMwExtras.mat'; ...
'2014-08-15_1931_MK012_TMwExtras.mat'; ...
'2014-08-02_2203_MK014_TMwExtras.mat'; ...
'2014-08-05_1937_MK014_TMwExtras.mat'; ...
};
vglutDatasets = {...
'2017-06-12_1420_JL005_TMwExtras.mat'; ...
'2017-07-15_1708_JL008_TMwExtras.mat'; ...
'2017-07-27_1433_JL008_TMwExtras.mat'; ...
'2017-08-12_1056_JL008_TMwExtras.mat'; ...
'2017-09-18_1707_JL008_TMwExtras.mat'; ...
'2017-09-23_1539_JL008_TMwExtras.mat'; ...
};
tripleDatasets = {...
'2015-07-03_2127_MK020_TMwExtras.mat'; ...
'2015-07-07_2127_MK020_TMwExtras.mat'; ...
'2015-07-30_2010_MK020_TMwExtras.mat'; ...
'2015-07-31_1851_MK020_TMwExtras.mat'; ...
'2015-08-02_1709_MK020_TMwExtras.mat'; ...
'2015-08-05_1930_MK020_TMwExtras.mat'; ...
'2015-08-07_1821_MK020_TMwExtras.mat'; ...
};
allPPC = [aavDatasets; tripleDatasets; vglutDatasets];
allFiles = dir(sprintf('%s*_TMwExtras.mat', folder));
files{1} = allFiles(ismember({allFiles.name}, aavDatasets));
files{2} = allFiles(ismember({allFiles.name}, tripleDatasets));
files{3} = allFiles(ismember({allFiles.name}, vglutDatasets));
% idx = ismember({allFiles.name}, allPPC);
% % idx = ismember({allFiles.name}, '2017-09-23_1539_JL008_TMwExtras.mat');
% % idx = ismember({allFiles.name}, '2015-08-02_1709_MK020_TMwExtras.mat');
% idx = ismember({allFiles.name}, '2014-08-05_1937_MK014_TMwExtras.mat');
%
% files = mat2cell(allFiles(idx), ones(size(allFiles(idx))), 1);
nGroups = length(files);
groupName = {'AAV', '3tg', 'VGlut', 'All mice'};
% for iGroup = 1:nGroups
% groupName{iGroup} = files{iGroup}(1).name(1:21);
% end
groupName{nGroups+1} = 'All mice';
groups2plot = 1:length(groupName);
%%
tic
for iGroup = 1:nGroups
fprintf('group %1.0f/%1.0f\n', iGroup, nGroups);
nFiles = length(files{iGroup});
for iFile = 1:nFiles
fprintf('file %1.0f/%1.0f\n', iFile, nFiles);
try
load(fullfile(folder, files{iGroup}(iFile).name));
catch
warning(sprintf('failed to load %s \n', files{iGroup}(iFile).name))
continue
end
res{iGroup}(iFile) = getFitQuality(TM);
resFileName = fullfile(folder, 'Fig3Groups_EVNoOptZ_1.mat');
save(resFileName, 'res');
end
end
resFileName = fullfile(folder, 'Fig3Groups_EVNoOptZ_1.mat');
save(resFileName, 'res');
toc
%% load data
folder = 'G:\DATA\';
% resFileName = fullfile(folder, 'Fig3Groups_RhoNoOptZ_095.mat');
% resFileName = fullfile(folder, 'Fig3Groups_RhoUseOptZ_095.mat');
% resFileName = fullfile(folder, 'Fig3Groups_EVuseOptZ_095.mat');
resFileName = fullfile(folder, 'Fig3Groups_EVnoOptZ_095.mat');
% resFileName = fullfile(folder, 'comparisonRastersResMaxF.mat');
% resFileName = fullfile(folder, 'comparisonRastersRes.mat');
load(resFileName);
%% define some parameters
resFull = res;
resFull{end+1} = cell2mat(res);
zBinEdges = [0 110];
nZBins = numel(zBinEdges)-1;
rocThr = 0.95;
stdThr = 0;
%% plot rasters
axesLims = [-1 1];
for iGroup = groups2plot
rhoZThD = cell2mat({resFull{iGroup}.rhoZThD}');
rhoZTh = cell2mat({resFull{iGroup}.rhoZTh}');
rhoZD = cell2mat({resFull{iGroup}.rhoZD}');
zPeak = cell2mat({resFull{iGroup}.zPeak}');
nSessions = length(resFull{iGroup});
rocArea= [];
thetaStd = [];
for iSession = 1:nSessions
nCells = numel(resFull{iGroup}(iSession).zPeak);
rocTmp = nan(nCells, 1);
stdTmp = nan(nCells, 1);
for iCell = 1:nCells
iPlane = resFull{iGroup}(iSession).planeIdx(iCell);
rocTmp(iCell, 1) = interp1(resFull{iGroup}(iSession).zROC{iPlane}, ...
resFull{iGroup}(iSession).thROC{iPlane}, resFull{iGroup}(iSession).zPeak(iCell));
stdTmp(iCell, 1) = interp1(resFull{iGroup}(iSession).zROC{iPlane}, ...
resFull{iGroup}(iSession).thStd{iPlane}, resFull{iGroup}(iSession).zPeak(iCell));
end
rocArea = cat(1, rocArea, rocTmp);
thetaStd = cat(1, thetaStd, stdTmp);
end
for iZBin = 1:nZBins
figName = sprintf('%s, z = [%1.0f %1.0f], roc < %4.2f', groupName{iGroup}, zBinEdges(iZBin), zBinEdges(iZBin+1), rocThr);
figure('Name', figName, 'Position', [300 300 1200 400]);
% idx = zPeak>=zBinEdges(iZBin) & zPeak < zBinEdges(iZBin+1);
% idx = idx & rocArea<rocThr & thetaStd > stdThr;
idx = ~isnan(rhoZTh);
nSelectedCells = sum(idx);
subplot(1, 3, 1)
plot(rhoZTh(idx), rhoZD(idx), '.');
hold on;
plot(axesLims, axesLims, 'k:');
axis equal
xlim(axesLims)
ylim(axesLims)
plot([0 0], axesLims, 'k:', axesLims, [0 0], 'k:');
xlabel('f(z, \theta)');
ylabel('f(z, d)')
box off;
text(0.1, 0.9, sprintf('nCells = %1.0f', nSelectedCells), ...
'HorizontalAlignment', 'left', 'VerticalAlignment', 'top', 'FontSize', 16)
subplot(1, 3, 2)
plot(rhoZThD(idx), rhoZTh(idx), '.');
hold on;
plot(axesLims, axesLims, 'k:');
axis equal
xlim(axesLims)
ylim(axesLims)
plot([0 0], axesLims, 'k:', axesLims, [0 0], 'k:');
xlabel('f(z, d, \theta)')
ylabel('f(z, \theta)');
title(figName);
box off;
subplot(1, 3, 3)
plot(rhoZThD(idx), rhoZD(idx), '.');
hold on;
plot(axesLims, axesLims, 'k:');
axis equal
xlim(axesLims)
ylim(axesLims)
plot([0 0], axesLims, 'k:', axesLims, [0 0], 'k:');
xlabel('f(z, d, \theta)');
ylabel('f(z, d)')
box off;
end
end
%% plot densities with histograms
dr = 0.005;
smoothing = 3;
edges{1} = -1:dr:1;
edges{2} = edges{1};
axesLims = [-1 1];
drHist = 0.02;
edgesHist = -1:drHist:1;
doLogScale = false;
% centres =
cMin = Inf;
cMax = -Inf;
for iGroup = groups2plot
rhoZThD = cell2mat({resFull{iGroup}.rhoZThD}');
rhoZTh = cell2mat({resFull{iGroup}.rhoZTh}');
rhoZD = cell2mat({resFull{iGroup}.rhoZD}');
zPeak = cell2mat({resFull{iGroup}.zPeak}');
nSessions = length(resFull{iGroup});
rocArea= [];
thetaStd = [];
for iSession = 1:nSessions
nCells = numel(resFull{iGroup}(iSession).zPeak);
rocTmp = nan(nCells, 1);
stdTmp = nan(nCells, 1);
for iCell = 1:nCells
iPlane = resFull{iGroup}(iSession).planeIdx(iCell);
rocTmp(iCell, 1) = interp1(resFull{iGroup}(iSession).zROC{iPlane}, ...
resFull{iGroup}(iSession).thROC{iPlane}, resFull{iGroup}(iSession).zPeak(iCell));
stdTmp(iCell, 1) = interp1(resFull{iGroup}(iSession).zROC{iPlane}, ...
resFull{iGroup}(iSession).thStd{iPlane}, resFull{iGroup}(iSession).zPeak(iCell));
end
rocArea = cat(1, rocArea, rocTmp);
thetaStd = cat(1, thetaStd, stdTmp);
end
for iZBin = 1:nZBins
% idx = zPeak>=zBinEdges(iZBin) & zPeak < zBinEdges(iZBin+1);
% idx = idx & rocArea<rocThr & thetaStd > stdThr;
idx = ~isnan(rhoZTh);
[N, C] = hist3([rhoZD(idx), rhoZTh(idx)], 'Edges', edges);
N = imgaussfilt(N, smoothing);
N = N/sum(N(:))/dr^2;
if doLogScale
N = log10(N+1);
end
cMin = min(cMin, min(N(:)));
cMax = max(cMax, max(N(:)));
[N, C] = hist3([rhoZThD(idx), rhoZTh(idx)], 'Edges', edges);
N = imgaussfilt(N, smoothing);
N = N/sum(N(:))/dr^2;
if doLogScale
N = log10(N+1);
end
cMin = min(cMin, min(N(:)));
cMax = max(cMax, max(N(:)));
[N, C] = hist3([rhoZD(idx), rhoZThD(idx)], 'Edges', edges);
N = imgaussfilt(N, smoothing);
N = N/sum(N(:))/dr^2;
if doLogScale
N = log10(N+1);
end
cMin = min(cMin, min(N(:)));
cMax = max(cMax, max(N(:)));
end
end
for iGroup = groups2plot
rhoZThD = cell2mat({resFull{iGroup}.rhoZThD}');
rhoZTh = cell2mat({resFull{iGroup}.rhoZTh}');
rhoZD = cell2mat({resFull{iGroup}.rhoZD}');
zPeak = cell2mat({resFull{iGroup}.zPeak}');
nSessions = length(resFull{iGroup});
% rocArea= [];
% thetaStd = [];
% for iSession = 1:nSessions
% nCells = numel(resFull{iGroup}(iSession).zPeak);
% rocTmp = nan(nCells, 1);
% stdTmp = nan(nCells, 1);
% for iCell = 1:nCells
% iPlane = resFull{iGroup}(iSession).planeIdx(iCell);
% rocTmp(iCell, 1) = interp1(resFull{iGroup}(iSession).zROC{iPlane}, ...
% resFull{iGroup}(iSession).thROC{iPlane}, resFull{iGroup}(iSession).zPeak(iCell));
% stdTmp(iCell, 1) = interp1(resFull{iGroup}(iSession).zROC{iPlane}, ...
% resFull{iGroup}(iSession).thStd{iPlane}, resFull{iGroup}(iSession).zPeak(iCell));
% end
% rocArea = cat(1, rocArea, rocTmp);
% thetaStd = cat(1, thetaStd, stdTmp);
% end
%
for iZBin = 1:nZBins
figName = sprintf('%s, z = [%1.0f %1.0f], AuROC < %4.2f, std_\\theta > %4.2f', groupName{iGroup}, zBinEdges(iZBin), zBinEdges(iZBin+1), rocThr, stdThr);
figure('Name', figName, 'Position', [300 300 1200 750]);
cm = colormap('bone');
colormap(flipud(cm));
% idx = zPeak>=zBinEdges(iZBin) & zPeak < zBinEdges(iZBin+1);
% idx = idx & rocArea<rocThr & thetaStd > stdThr;
idx = ~isnan(rhoZTh);
nSelectedCells = sum(idx);
ax = subplot(2, 3, 1);
[N, C] = hist3([rhoZD(idx), rhoZTh(idx)], 'Edges', edges);
N = imgaussfilt(N, smoothing);
N = N/sum(N(:))/dr^2;
if doLogScale
N = log10(N+1);
end
imagesc(C{2}(1:end-1), C{1}(1:end-1), N(1:end-1, 1:end-1));
hold on;
plot(axesLims, axesLims, 'r--', 'LineWidth', 1);
axis equal xy
xlim(axesLims)
ylim(axesLims)
plot([0 0], axesLims, 'k:', axesLims, [0 0], 'k:');
xlabel('\rho_{z,\theta}');
ylabel('\rho_{z,d}')
% caxis([cMin cMax]);
box off;
ax.XTick = [0, 0.5, 1];
ax.YTick = [0, 0.5, 1];
ax.FontSize = 14;
text(0.1, 0.9, sprintf('nCells = %1.0f', nSelectedCells), ...
'HorizontalAlignment', 'left', 'VerticalAlignment', 'top', 'FontSize', 16)
ax = subplot(2, 3, 4);
[counts, centers] = hist(rhoZTh(idx)-rhoZD(idx), -1:drHist:1);
c50 = prctile(rhoZTh(idx)-rhoZD(idx), 50);
cm = nanmean(rhoZTh(idx)-rhoZD(idx));
counts = counts/sum(counts(:))/drHist/2;
% stairs(centers, log10(counts+1));
stairs(centers, counts);
hold on;
% plot([c50 c50], ylim, 'r--')
% plot([cm cm], ylim, 'g--')
axis tight
plot([0 0], ylim, 'k:')
xlim([-0.5 0.5]);
% legend('', 'p50', 'mean')
xlabel('\rho_{z,\theta} - \rho_{z,d}');
box off;
ax.YTick = [];
ax.FontSize = 14;
ax = subplot(2, 3, 2);
[N, C] = hist3([rhoZTh(idx), rhoZThD(idx)], 'Edges', edges);
N = imgaussfilt(N, smoothing);
N = N/sum(N(:))/dr^2;
if doLogScale
N = log10(N+1);
end
imagesc(C{2}(1:end-1), C{1}(1:end-1), N(1:end-1, 1:end-1));
hold on;
plot(axesLims, axesLims, 'r--', 'LineWidth', 1);
axis equal xy
xlim(axesLims)
ylim(axesLims)
plot([0 0], axesLims, 'k:', axesLims, [0 0], 'k:');
xlabel('\rho_{z,d,\theta}')
ylabel('\rho_{z,\theta}');
% caxis([cMin cMax]);
box off;
title(figName);
ax.XTick = [0, 0.5, 1];
ax.YTick = [0, 0.5, 1];
ax.FontSize = 14;
ax = subplot(2, 3, 5);
[counts, centers] = hist(rhoZThD(idx)-rhoZTh(idx), -1:drHist:1);
c50 = prctile(rhoZTh(idx)-rhoZD(idx), 50);
cm = nanmean(rhoZTh(idx)-rhoZD(idx));
counts = counts/sum(counts(:))/drHist/2;
% stairs(centers, log10(counts+1));
stairs(centers, counts);
hold on;
% plot([c50 c50], ylim, 'r--')
% plot([cm cm], ylim, 'g--')
box off;
ax.YTick = [];
ax.FontSize = 14;
axis tight
plot([0 0], ylim, 'k:')
xlim([-0.5 0.5]);
xlabel('\rho_{z,d,\theta} - \rho_{z,\theta}')
ax = subplot(2, 3, 3);
[N, C] = hist3([rhoZD(idx), rhoZThD(idx)], 'Edges', edges);
N = imgaussfilt(N, smoothing);
N = N/sum(N(:))/dr^2;
if doLogScale
N = log10(N+1);
end
imagesc(C{2}(1:end-1), C{1}(1:end-1), N(1:end-1, 1:end-1));
hold on;
plot(axesLims, axesLims, 'r--', 'LineWidth', 1);
axis equal xy
xlim(axesLims)
ylim(axesLims)
plot([0 0], axesLims, 'k:', axesLims, [0 0], 'k:');
xlabel('\rho_{z,d,\theta}');
ylabel('\rho_{z,d}')
% caxis([cMin cMax]);
box off;
ax.XTick = [0, 0.5, 1];
ax.YTick = [0, 0.5, 1];
ax.FontSize = 14;
ax = subplot(2, 3, 6);
[counts, centers] = hist(rhoZThD(idx)-rhoZD(idx), -1:drHist:1);
c50 = prctile(rhoZTh(idx)-rhoZD(idx), 50);
cm = nanmean(rhoZTh(idx)-rhoZD(idx));
counts = counts/sum(counts(:))/drHist/2;
% stairs(centers, log10(counts+1));
stairs(centers, counts);
hold on;
% plot([c50 c50], ylim, 'r--')
% plot([cm cm], ylim, 'g--')
axis tight
plot([0 0], ylim, 'k:')
xlim([-0.5 0.5]);
xlabel('\rho_{z,d,\theta} - \rho_{z,d}');
box off;
ax.YTick = [];
ax.FontSize = 14;
end
end