Figure2Addon.m

load('G:\DATA\TM_2014-08-15_MK012.mat')
load('G:\DATA\RES_2014-08-15_MK012_cv10_dt0.00.mat')

TM = TM.TMVR;
res = RES.TMVR.res;

iPlane = 4;
iROI = 4;

map = res{iPlane}(iROI).zThetaMap;
zAxis = res{iPlane}(iROI).zThetaBinCentres{1};
thAxis = res{iPlane}(iROI).zThetaBinCentres{2};

fData = TM.data2p{iPlane}.F(:, iROI);
f0 = prctile(fData, 20);
fData = (fData-f0)/f0;
tData = TM.times2p{iPlane}';

contrasts = TM.dataTMaze.contrastSequence;
report = TM.dataTMaze.report';
cc = unique(contrasts);
nRows = 2;
nColumns = length(cc);

nTrials = TM.dataTMaze.nTrials;
hFig = figure;
hFig.Color = [1 1 1];

for iTrial = 1:nTrials
    if ~ismember(report(iTrial), 'RL')
        % we only want finished trials
        continue;
    end
    t = TM.timesVRframes(iTrial).t(2:end-1);
    if isempty(t)
        continue;
    end
    idx = TM.timesVRframes(iTrial).idx(2:end);
    z = -TM.dataTMaze.SESSION.allTrials(iTrial).posdata(idx,3);
    theta = 180/pi*TM.dataTMaze.SESSION.allTrials(iTrial).posdata(idx,4);
    f = interp1(tData, fData, t);
    
    iRow = 1*(report(iTrial) == 'L') + 2*(report(iTrial) == 'R');
    iColumn = find(cc == contrasts(iTrial));
    iPlot = sub2ind([nColumns, nRows], iColumn, iRow);
%     if iPlot ~= 1
%         continue;
%     end
    subplot(nRows, nColumns, iPlot)
    theta = theta(1:10:end);
    z = z(1:10:end);
    f = f(1:10:end);
%     s = surface([theta, theta]', [z, z]', 0*[z, z]', [f, f]');
%     s.EdgeColor = 'interp';
%     s.LineWidth = 1;

    theta(end+1) = NaN;
    z(end+1) = NaN;
    f(end+1) = NaN;
    p = patch(theta, z, f);
    p.EdgeColor = 'interp';
    p.LineWidth = 1;

    hold on;
    if iRow == 1
        title(sprintf('%1.0f%%', contrasts(iTrial)));
        set(gca, 'XTickLabel', '')
    end
    if iRow == 2 && iColumn == 1
        lbl = xlabel('\theta [deg]');
        lbl.FontSize = 12;
    end
    if iColumn == 1
        lbl = ylabel('z [cm]');
        lbl.FontSize = 12;
    else
        set(gca, 'YTickLabel', '')
        set(gca, 'XTickLabel', '')
    end
end

cminmax = prctile(fData, [0.1 99.9]);
cminmax = [0 2]; % to match the existing figure
thr = mean(prctile(fData, [0.1 99.9]));
% thr = 1;
% thr = min(map(:)) + 0.6*(max(map(:))-min(map(:)));
cont = contourc(thAxis, zAxis, map, [thr thr]);
cX = cont(1, 2:end);
cX(end+1) = cX(1);
cY = cont(2, 2:end);
cY(end+1) = cY(1);

ax = hFig.Children;
for iAx = 1:length(ax)
    colormap(ax(iAx), 'jet');
    caxis(ax(iAx), cminmax);
%     ax(iAx).XLim = ([min(thAxis), max(thAxis)]);
    ax(iAx).XLim = ([-30, 30]);
    ax(iAx).YLim = ([0, max(zAxis)]);
    ax(iAx).DataAspectRatio = [1 1 1];
    ax(iAx).XTick = [-30 0 30];
    ax(iAx).YTick = [0 50 100];
    ax(iAx).FontSize = 14;
%     plot(ax(iAx), cX, cY, 'k--', 'LineWidth', 2);
end

figure;
set(gcf, 'Color', [1 1 1]);
for iTrial = 1:nTrials
    t = TM.timesVRframes(iTrial).t(2:end-1);
    if isempty(t)
        continue;
    end
    idx = TM.timesVRframes(iTrial).idx(2:end);
    z = -TM.dataTMaze.SESSION.allTrials(iTrial).posdata(idx,3);
    theta = 180/pi*TM.dataTMaze.SESSION.allTrials(iTrial).posdata(idx,4);
    plot(theta, z, 'b', 'LineWidth', 0.25);
    hold on;
end
im = imagesc(thAxis, zAxis, map);
axis equal tight
caxis(cminmax);
axis xy
colormap jet
set(gca, 'XTick', [-30 0 30]);
set(gca, 'YTick', [0 50 100]);
hold on;
plot(cX, cY, 'k--', 'LineWidth', 2);
xlabel('\theta [deg]');
ylabel('z [cm]');
im.AlphaData = 0.8;
set(gca, 'FontSize', 14);