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PlotCurated.m
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PlotCurated.m
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function PlotCurated(varargin)
%
% Author: Sid Henriksen (2015). Email: [email protected].
%
% Note, the code for this browser is not well-documented, nor is it
% intended to be. The README file in the repo documents the structure
% of the CuratedCells.mat file, which this script uses.
%
% Create figure
myFig=figure();
mh = uimenu(myFig,'Label','Plot');
mainx = uimenu(mh,'Label','Main: x axis');
mainy = uimenu(mh,'Label','Main: y axis');
% Takes optional for which curated cells file
if nargin > 0
load(varargin{1});
ddmax = 2;
else
load('CuratedCells.mat');
ddmax = 2;
end
densities = cat(1,Base.density);
% This is included just for the sake of colors
fileNames = {};
myCols = [1,0,0;0,1,0;0,0,1;1,1,0;1,0,1;0,1,1;rand(15,3)];
monkeys = {'jbe','lem'};
setappdata(myFig,'Base',Base);
% This first segment defines the menus; all call make_subplots to
% populate the subplots, together with Base (consisting of all the
% data) and a string which specifies what we're plotting.
% X menu
menux_CHMr = uimenu(mainx,'Label','Half-matched r','Checked', 'on','Callback',{@make_subplots,Base,'CHMr'});
menux_CACr = uimenu(mainx,'Label','Anticorrelated r','Checked', 'off','Callback',{@make_subplots,Base,'CACr'});
menux_CMeanr = uimenu(mainx,'Label','Mean CAC r','Checked', 'off','Callback',{@make_subplots,Base,'CMeanr'});
menux_CHMslope = uimenu(mainx,'Label','Half-matched slope','Checked', 'off','Callback',{@make_subplots,Base,'CHMslope'});
menux_CACslope = uimenu(mainx,'Label','Anticorrelated slope','Checked', 'off','Callback',{@make_subplots,Base,'CACslope'});
menux_CMeanslope = uimenu(mainx,'Label','Mean CAC slope','Checked', 'off','Callback',{@make_subplots,Base,'CMeanslope'});
menux_HMCACslope = uimenu(mainx,'Label','Mean CAC slope/HM slope','Checked', 'off','Callback',{@make_subplots,Base,'HMCACslope'});
%%% ROC menu
menux_ROC = uimenu(mainx,'Label','ROC/d''');
menux_HMauc = uimenu(menux_ROC,'Label','Half-matched AUC','Checked', 'off','Callback',{@make_subplots,Base,'HM AUC'});
menux_HMaucZ = uimenu(menux_ROC,'Label','Half-matched AUC (Z-score)','Checked', 'off','Callback',{@make_subplots,Base,'HM AUC Z'});
menux_HMdprime = uimenu(menux_ROC,'Label','Half-matched d''','Checked', 'off','Callback',{@make_subplots,Base,'HM d'''});
menux_Cauc = uimenu(menux_ROC,'Label','Correlated AUC','Checked', 'off','Callback',{@make_subplots,Base,'C AUC'});
menux_CaucZ = uimenu(menux_ROC,'Label','Correlated AUC (Z-score)','Checked', 'off','Callback',{@make_subplots,Base,'C AUC Z'});
menux_Cdprime = uimenu(menux_ROC,'Label','Correlated d''','Checked', 'off','Callback',{@make_subplots,Base,'C d'''});
% Y menu
menuy_CHMr = uimenu(mainy,'Label','Half-matched r','Checked', 'on','Callback',{@make_subplots,Base,'CHMr'});
menuy_CACr = uimenu(mainy,'Label','Anticorrelated r','Checked', 'off','Callback',{@make_subplots,Base,'CACr'});
menuy_CMeanr = uimenu(mainy,'Label','Mean CAC r','Checked', 'off','Callback',{@make_subplots,Base,'CMeanr'});
menuy_CHMslope = uimenu(mainy,'Label','Half-matched slope','Checked', 'off','Callback',{@make_subplots,Base,'CHMslope'});
menuy_CACslope = uimenu(mainy,'Label','Anticorrelated slope','Checked', 'off','Callback',{@make_subplots,Base,'CACslope'});
menuy_CMeanslope = uimenu(mainy,'Label','Mean CAC slope','Checked', 'off','Callback',{@make_subplots,Base,'CMeanslope'});
menuy_HMCACslope = uimenu(mainy,'Label','Mean CAC slope/HM slope','Checked', 'off','Callback',{@make_subplots,Base,'HMCACslope'});
%%% ROC menu
menuy_ROC = uimenu(mainy,'Label','ROC/d''');
menuy_HMauc = uimenu(menuy_ROC,'Label','Half-matched AUC','Checked', 'off','Callback',{@make_subplots,Base,'HM AUC'});
menuy_HMaucZ = uimenu(menuy_ROC,'Label','Half-matched AUC (Z-score)','Checked', 'off','Callback',{@make_subplots,Base,'HM AUC Z'});
menuy_HMdprime = uimenu(menuy_ROC,'Label','Half-matched d''','Checked', 'off','Callback',{@make_subplots,Base,'HM d'''});
menuy_Cauc = uimenu(menuy_ROC,'Label','Correlated AUC','Checked', 'off','Callback',{@make_subplots,Base,'C AUC'});
menuy_CaucZ = uimenu(menuy_ROC,'Label','Correlated AUC (Z-score)','Checked', 'off','Callback',{@make_subplots,Base,'C AUC Z'});
menuy_Cdprime = uimenu(menuy_ROC,'Label','Correlated d''','Checked', 'off','Callback',{@make_subplots,Base,'C d'''});
% Misc
menuPlotDDIROC = uimenu(mh,'Label','DDI-ROC','Callback',{@make_auc_plot});
menuStats = uimenu(mh,'Label','Stats','Callback',{@show_stats,Base});
menuPenetrations = uimenu(mh,'Label','Penetrations','Callback',{@plot_penetrations,Base});
menuRank = uimenu(mh,'Label','Rank','Callback',{@PlotRank});
menuSmile = uimenu(mh,'Label','Smile','Callback',{@smile});
% This section initializes the plot and figure data
count = 0;
for dd = [1,ddmax];
count = count+1;
currentData = Base(dd).Cells;
subplot(1,2,count);
setappdata(gca,'subplot',count);
setappdata(gca,'density',Base(dd).density);
% Set the x and y axis data
setappdata(myFig,'xdata','CHMr');
setappdata(myFig,'ydata','CACr');
setappdata(myFig,'xy_errorbars',0);
make_subplots(myFig,NaN,Base,'Correlation');
end
set(gcf,'Color','White','windowbuttondownfcn',{@TC_callback},'windowkeypressfcn',{@keydown_callback});
end
function make_subplots(myFig,evt,Base,type)
% Function to populate the subplots of the main figure
% This will take Base, which is the structure generated by
% CurateCells.m, and a string as argument. The string should specify
% what we're plotting on the relevant axis.
count = 0;
ddmax = length(Base);
ch = get(gcf,'Children');
% This doesn't work for older version of Matlab; I don't have easy
% access to an older version so debugging becomes a bit tricky.
plotMenu = get(ch(1),'Children');
xmainMenu = plotMenu(length(plotMenu));
ymainMenu = plotMenu(length(plotMenu)-1);
xmainChildren = get(xmainMenu,'Children');
ymainChildren = get(ymainMenu,'Children');
axchange = '';
if ~isempty(events(evt));
rootMenu = evt.Source.Parent;
if strcmp(rootMenu.Label,'Main: x axis');
setappdata(gcf,'xdata',type)
axchange = 'x';
elseif strcmp(rootMenu.Label,'Main: y axis');
setappdata(gcf,'ydata',type);
axchange = 'y';
else
rootMenu = rootMenu.Parent;
if strcmp(rootMenu.Label,'Main: x axis');
setappdata(gcf,'xdata',type)
axchange = 'x';
elseif strcmp(rootMenu.Label,'Main: y axis');
setappdata(gcf,'ydata',type);
axchange = 'y';
end
%error('Error: This isn''t supposed to happen');
end
end
for dd = [1,ddmax];
count = count+1;
currentData = Base(dd).Cells;
subplot(1,2,count);
setappdata(gca,'subplot',count);
setappdata(gca,'density',Base(dd).density);
plot_data(currentData);
% Adjust the ticks appropriately
if strcmp(axchange,'x');
mainChildren = xmainChildren;
elseif strcmp(axchange,'y');
mainChildren = ymainChildren;
end
if ~strcmp(axchange,'');
for k = 1:length(mainChildren);
current = mainChildren(k);
if strcmp(current.Label,evt.Source.Label);
current.Checked = 'on';
else
current.Checked = 'off';
end
end
end
end
end
function plot_data(currentData);
% This is a function that actually plots the data in the highlighted
% subplot. This function will take the figure data that has been set
% elsewhere and will plot the correct thing. This is really lengthy.
monkeys = {'jbe','lem'};
myFig = gcf;
figAppdata = getappdata(myFig);
axAppdata = getappdata(gca);
allExptNames = figAppdata.Base(1).exptlist;
% If colours are not defined, define them. Otherwise just get them
% from appdata
if ~isfield(figAppdata,'colors');
myCols = [1,0,0;0,1,0;0,0,1;1,1,0;1,0,1;0,1,1;rand(20,3).^2];
setappdata(gcf,'colors',myCols);
else
myCols = figAppdata.colors;
end
nCells = length(currentData);
fileNames = {};
cla;
hold on;
X = zeros(1,nCells);
Y = zeros(1,nCells);
xtype = getappdata(gcf,'xdata');
ytype = getappdata(gcf,'ydata');
lambda = 1/sqrt(10);
for cell = 1:nCells
whichFile = strcmp(currentData(cell).filename,allExptNames);
currentColor = myCols(whichFile,:);
% Skip if we have NaNs...
if ~isnan(currentData(cell).DDI);
currentMonkey = currentData(cell).filename(9:11);
% We choose from a range of data types to plot;
% This is really long, but simply chooses the correct values
% to plot on the x and y axes.
switch xtype
case 'CHMr'
x = currentData(cell).regHmRegular(1);
case 'CACr'
x = currentData(cell).regAcRegular(1);
case 'CMeanr'
corrResp = currentData(cell).correlatedResponse';
meanCACResp = (currentData(cell).correlatedResponse+ ...
currentData(cell).anticorrelatedResponse)'/2;
[x,~,~] = regression2(meanCACResp,corrResp);
%[~,x,~] = fit_bothsubj2error(corrResp,meanCACResp,lambda);
case 'CHMslope'
x = currentData(cell).regHm(2);
case 'CACslope'
x = currentData(cell).regAc(2);
case 'CMeanslope'
corrResp = currentData(cell).correlatedResponse';
meanCACResp = (currentData(cell).correlatedResponse+ ...
currentData(cell).anticorrelatedResponse)'/2;
[~,x,~] = regression2(meanCACResp,corrResp);
case 'HMCACslope'
corrResp = currentData(cell).correlatedResponse';
hmResp = currentData(cell).halfmatchedResponse';
meanCACResp = (currentData(cell).correlatedResponse+ ...
currentData(cell).anticorrelatedResponse)'/2;
[~,hmslope,~] = regression2(hmResp,corrResp); % Change this to fit_bothsubj2error?
[~,meanCACslope,~] = regression2(meanCACResp,corrResp);
x = hmslope/meanCACslope;
case 'HM AUC';
x = currentData(cell).HMauc;
case 'HM AUC Z';
x = currentData(cell).HMaucZ;
case 'HM d''';
x = currentData(cell).HMdprime;
case 'C AUC';
x = currentData(cell).Cauc;
case 'C AUC Z';
x = currentData(cell).CaucZ;
case 'C d''';
x = currentData(cell).Cdprime;
end
switch ytype
case 'HM AUC';
y = currentData(cell).HMauc;
case 'HM d''';
y = currentData(cell).HMdprime;
case 'CHMr'
y = currentData(cell).regHmRegular(1);
case 'CACr'
y = currentData(cell).regAcRegular(1);
case 'CMeanr'
corrResp = currentData(cell).correlatedResponse';
meanCACResp = (currentData(cell).correlatedResponse+ ...
currentData(cell).anticorrelatedResponse)'/2;
[y,~,~] = regression2(meanCACResp,corrResp);
case 'CHMslope'
y = currentData(cell).regHm(2);
case 'CACslope'
y = currentData(cell).regAc(2);
case 'CMeanslope'
corrResp = currentData(cell).correlatedResponse';
meanCACResp = (currentData(cell).correlatedResponse+ ...
currentData(cell).anticorrelatedResponse)'/2;
[~,y,~] = regression2(meanCACResp,corrResp);
case 'HMCACslope'
corrResp = currentData(cell).correlatedResponse';
hmResp = currentData(cell).halfmatchedResponse';
meanCACResp = (currentData(cell).correlatedResponse+ ...
currentData(cell).anticorrelatedResponse)'/2;
[~,hmslope,~] = regression2(hmResp,corrResp); % Change this to fit_bothsubj2error?
[~,meanCACslope,~] = regression2(meanCACResp,corrResp);
y = hmslope/meanCACslope; % Change this to fit_bothsubj2error?
case 'HM AUC';
y = currentData(cell).HMauc;
case 'HM AUC Z';
y = currentData(cell).HMaucZ;
case 'HM d''';
y = currentData(cell).HMdprime;
case 'C AUC';
y = currentData(cell).Cauc;
case 'C AUC Z';
y = currentData(cell).CaucZ;
case 'C d''';
y = currentData(cell).Cdprime;
end
% Get errorbar data
xbar = []; ybar = [];
errorbars_on=getappdata(myFig,'xy_errorbars');
if errorbars_on
switch xtype
case 'CHMr'
xbar = currentData(cell).CHm_r_CI;
case 'CACr'
xbar = currentData(cell).CAc_r_CI;
case 'CHMslope'
xbar = currentData(cell).CHm_slope_CI;
case 'CACslope'
xbar = currentData(cell).CAc_slope_CI;
end
switch ytype
case 'CHMr'
ybar = currentData(cell).CHm_r_CI;
case 'CACr'
ybar = currentData(cell).CAc_r_CI;
case 'CHMslope'
ybar = currentData(cell).CHm_slope_CI;
case 'CACslope'
ybar = currentData(cell).CAc_slope_CI;
end
end
%% This is where we actually plot the data
% Different shapes for jbe and lem
if strcmp(currentMonkey,monkeys{1});
plot(x,y,'k','marker','s','markersize',...
round(1+currentData(cell).DDI*20),'markerfacecolor',currentColor);
if ~isempty(xbar);
xbar = abs(xbar-x);
E=herrorbar(x,y,xbar(1),xbar(2));
set(E,'linewidth',2,'color',currentColor);
end
if ~isempty(ybar);
ybar = abs(ybar-y);
E = errorbar(x,y,ybar(1),ybar(2));
set(E,'linewidth',2,'color',currentColor);
end
elseif strcmp(currentMonkey,monkeys{2});
plot(x,y,'k','marker','o','markersize', ...
round(1+currentData(cell).DDI*20),'markerfacecolor',currentColor);
if ~isempty(xbar);
xbar = abs(xbar-x);
E=herrorbar(x,y,xbar(1),xbar(2));
set(E,'linewidth',2,'color',currentColor);
end
if ~isempty(ybar);
ybar = abs(ybar-y);
E = errorbar(x,y,ybar(1),ybar(2));
set(E,'linewidth',2,'color',currentColor);
end
end
X(cell) = x;
Y(cell) = y;
end
end
% Again, very lengty, but simply chooses appropriate xlims/ylims and
% axis labels
switch xtype
case 'CHMr'
xlab = 'HM r';
xlims = [-1,1];
case 'CACr'
xlab = 'AC r';
xlims = [-1,1];
case 'CMeanr'
xlab = 'Mean CAC r';
xlims = [-0.2,1];
case 'CHMslope'
xlab = 'HM slope';
xlims = [-0.35,0.35];
case 'CACslope'
xlab = 'AC slope';
xlims = [-1,1];
case 'CMeanslope'
xlab = 'Mean CAC slope';
xlims = [-1,1];
case 'HMCACslope'
xlab = 'HM slope/mean CAC slope';
xlims = [-0.25,1.25];
case 'HM AUC'
xlab = 'Half-matched AUC';
xlims = [0,1];
case 'HM AUC Z'
xlab = 'Half-matched AUC (Z-score)';
xlims = [0,1];
case 'HM d'''
xlab = 'Half-matched d''';
xlims = [-0.5,5];
case 'C AUC'
xlab = 'Correlated AUC';
xlims = [0,1];
case 'C AUC Z'
xlab = 'Correlated AUC (Z-score)';
xlims = [0,1];
case 'C d'''
xlab = 'Correlated d''';
xlims = [-0.5,10];
end
switch ytype
case 'CHMr'
ylab = 'HM r';
ylims = [-1,1];
case 'CACr'
ylab = 'Anticorrelated r';
ylims = [-1,1];
case 'CMeanr'
ylab = 'Mean CAC r';
ylims = [-0.2,1];
case 'CHMslope'
ylab = 'HM slope';
ylims = [-0.35,0.35];
case 'CACslope'
ylab = 'AC slope';
ylims = [-1,1];
case 'CMeanslope' %for half-matched and anticorrelated
ylab = 'Mean CAC slope';
ylims = [-1,1];
case 'HMCACslope'
ylab = 'HM slope/mean CAC slope';
ylims = [-0.25,1.25];
case 'HM AUC'
ylab = 'Half-matched AUC';
ylims = [0,1];
case 'HM AUC Z'
ylab = 'Half-matched AUC (Z-score)';
ylims = [0,1];
case 'HM d'''
ylab = 'Half-matched d''';
ylims = [-0.5,5];
case 'C AUC'
ylab = 'Correlated AUC';
ylims = [0,1];
case 'C AUC Z'
ylab = 'Correlated AUC (Z-score)';
ylims = [0,1];
case 'C d'''
ylab = 'Correlated d''';
ylims = [-0.5,10];
end
% Select appropriate ticks for purteh lookin' plot
if ~isempty(strfind(xtype,'d'''));
xticks = -1:2:10;
else
xticks = -1:0.5:1;
end
if ~isempty(strfind(ytype,'d'''));
yticks = -1:2:10;
else
yticks = -1:0.5:1;
end
% Set XYData!
XYData.x = X;
XYData.y = Y;
setappdata(gca,'XYData',XYData);
setappdata(gca,'Cells',currentData);
xlabel(xlab,'fontsize',20)
ylabel(ylab, 'fontsize', 20);
ylim(ylims);
xlim(xlims);
set(gca,'XTick',xticks,'fontsize',18);
set(gca,'YTick',yticks,'fontsize',18);
if isfield(axAppdata,'density');
title(sprintf('Density: %i%', axAppdata.density),'fontsize', 24);
else
title('Density unknown','fontsize',18);
end
% Put some text in the window showing how many cells
jbeCount = 0;
lemCount = 0;
for j = 1:nCells
jbeCount = jbeCount + strcmp(currentData(j).filename(9:11),'jbe');
lemCount = lemCount + strcmp(currentData(j).filename(9:11),'lem');
end
text(0.4,0.8,['jbe: ',num2str(jbeCount),' cells']);
text(0.4,0.7,['lem: ',num2str(lemCount),' cells']);
% Draw some lines to split into quadrants; where to draw this depends
% on what we're plotting
if ~isempty(strfind(ytype,'AUC'));
plot([-20,20],[0.5,0.5],'linewidth',1,'color','red','linestyle','--');
else
plot([-20,20],[0,0],'linewidth',1,'color','red','linestyle','--');
end
if ~isempty(strfind(xtype,'AUC'));
plot([0.5,0.5],[-20,20],'linewidth',1,'color','red','linestyle','--');
else
plot([0,0],[-20,20],'linewidth',1,'color','red','linestyle','--');
end
end
function TC_callback(myFig,evt,varargin);
% Callback function to plot tuning curves
figData = getappdata(myFig);
% If this hasn't been called before, assign a new figure handle
if isfield(figData,'TCHandle');
tcFigDeleted = ~ishandle(figData.TCHandle);
end
if ~isfield(figData,'TCHandle') || tcFigDeleted;
newFig = figure(); setappdata(newFig,'plotCAC','Off');
set(newFig,'color','white');
figData.TCHandle = newFig;
setappdata(myFig,'TCHandle',newFig);
setappdata(myFig,'Errorbars','Off');
setappdata(figData.TCHandle,'PseudoParent',myFig);
toggleMenu = uimenu(figData.TCHandle,'Label','Toggle');
toggleErrorbarsSEM = uimenu(toggleMenu,'Label','SEM error bars (95% CIs)','Checked','off','Callback',{@set_errorbars,myFig,evt,'SEM'});
toggleErrorbarsSD = uimenu(toggleMenu,'Label','Error bars (+/- 1 SD)','Checked','off','Callback',{@set_errorbars,myFig,evt,'SD'});
toggleErrorbarsBootstrap = uimenu(toggleMenu,'Label','Bootstrap error bars (95% CIs)','Checked','off','Callback',{@set_errorbars,myFig,evt,'bootstrap'});
setappdata(figData.TCHandle,'ErrorbarsToggled','None');
end
errorbarsToggled = getappdata(figData.TCHandle,'ErrorbarsToggled');
currentAxis = myFig.CurrentAxes;
axisData = getappdata(currentAxis);
currentPoint = get(currentAxis,'currentpoint');
% Get data
Cells = axisData.Cells;
XYData = axisData.XYData;
subplotNumber = axisData.subplot;
% Find point with closest Euclidean distance
distance = (XYData.x-currentPoint(1,1)).^2 + (XYData.y - currentPoint(2,2)).^2;
if nargin == 2
whichCell = find(distance == min(distance));
whichCell = whichCell(1); % If equidistant, just choose first one
else
otherID = varargin{1};
for j = 1:length(Cells);
uniqueID = quickhash([Cells(j).filename, num2str(Cells(j).cellnumber)]);
if uniqueID == otherID;
whichCell = j;
break
else
whichCell = 0;
end
end
end
figure(figData.TCHandle);
if subplotNumber > 2;
maxSubplots = subplotNumber;
else
maxSubplots = 2;
end
subplot(1,maxSubplots,subplotNumber); hold off;
if whichCell > 0;
cellName = [Cells(whichCell).filename(18:24),'-cell',num2str(Cells(whichCell).cellnumber)];
set(gca,'fontsize',18);
Dx = Cells(whichCell).Dx;
menus = get(figData.TCHandle,'Children');
toggleMenu = menus(1); errorbarMenu = toggleMenu.Children;
if ~any(strcmpi({errorbarMenu.Checked},'On'));
plot(Dx,Cells(whichCell).halfmatchedResponse*2.5,'b -- o', ...
Dx,Cells(whichCell).correlatedResponse*2.5,'r -- o', ...
Dx,Cells(whichCell).anticorrelatedResponse*2.5,'k -- o', ...
'linewidth',3,'markersize',5,'markerfacecolor','k');
else
barType = getappdata(figData.TCHandle,'ErrorbarsToggled');
switch barType
case 'SEM'
errorbarHM1 = Cells(whichCell).halfmatchedSEM*1.96;
errorbarHM2 = Cells(whichCell).halfmatchedSEM*1.96;
errorbarC1 = Cells(whichCell).correlatedSEM*1.96;
errorbarC2 = Cells(whichCell).correlatedSEM*1.96;
errorbarAC1 = Cells(whichCell).anticorrelatedSEM*1.96;
errorbarAC2 = Cells(whichCell).anticorrelatedSEM*1.96;
case 'SD'
errorbarHM1 = Cells(whichCell).halfmatchedSD;
errorbarHM2 = Cells(whichCell).halfmatchedSD;
errorbarC1 = Cells(whichCell).correlatedSD;
errorbarC2 = Cells(whichCell).correlatedSD;
errorbarAC1 = Cells(whichCell).anticorrelatedSD;
errorbarAC2 = Cells(whichCell).anticorrelatedSD;
case 'bootstrap'
%errorbarC1 = Cells(whichCell).ciLowC;
%errorbarC2 = Cells(whichCell).ciHighC;
%errorbarHM1 = Cells(whichCell).ciLowHm;
%errorbarHM2 = Cells(whichCell).ciHighHm;
%errorbarAC1 = Cells(whichCell).ciLowAc;
%errorbarAC2 = Cells(whichCell).ciHighAc;
errorbarC1 = Cells(whichCell).correlatedResponse-Cells(whichCell).ciLowC;
errorbarC2 = Cells(whichCell).ciHighC - Cells(whichCell).correlatedResponse;
errorbarHM1 = Cells(whichCell).halfmatchedResponse-Cells(whichCell).ciLowHm;
errorbarHM2 = Cells(whichCell).ciHighHm - Cells(whichCell).halfmatchedResponse;
errorbarAC1 = Cells(whichCell).anticorrelatedResponse-Cells(whichCell).ciLowAc;
errorbarAC2 = Cells(whichCell).ciHighAc - Cells(whichCell).anticorrelatedResponse;
end
E1=errorbar(Dx,Cells(whichCell).halfmatchedResponse*2.5,...
errorbarHM1*2.5,errorbarHM2*2.5);
set(E1,'linewidth',3,'color','b','marker','o','linestyle','--',...
'markersize',5,'markerfacecolor','b');
hold on;
E2=errorbar(Dx,Cells(whichCell).correlatedResponse*2.5,...
errorbarC1*2.5,errorbarC2*2.5);
set(E2,'linewidth',3,'color','r','marker','o','linestyle','--',...
'markersize',5,'markerfacecolor','r')
E3=errorbar(Dx,Cells(whichCell).anticorrelatedResponse*2.5,...
errorbarAC1*2.5,errorbarAC2*2.5);
set(E3,'linewidth',3,'color','k','marker','o','linestyle','--',...
'markersize',5,'markerfacecolor','k')
hold off;
end
elseif nargin > 2
cla
cellName = '';
else
error('Error: This shouldn''t happen...');
end
%cacMenu = uimenu(myFig,'Label','Plot CAC','Checked','Off','Callback',{@plot_CAC_in_TC_plot,);
xlabel('Disparity (deg)','fontsize',18);
ylabel('Spikes per second','fontsize',18);
density = (subplotNumber==1)*5 + (subplotNumber==2)*24;
title(['Density: ', num2str(density),'; ',cellName],'fontsize',22);
selectionType = get(myFig,'selectionType');
shiftPressed = strcmp(selectionType,'extend');
ctrlPressed = strcmp(selectionType,'alt');
% This will only get executed if uniqueID is not passed to TC_callback
% (which we only do when we call TC_callback recursively)
if shiftPressed || ctrlPressed
% If this hasn't been called before, assign a new figure handle
if isfield(figData,'scatterHandle');
figDeleted = ~ishandle(figData.scatterHandle);
end
if ~isfield(figData,'scatterHandle') || figDeleted;
scatterFig = figure();
set(scatterFig,'color','white');
figData.scatterHandle = scatterFig;
setappdata(myFig,'scatterHandle',scatterFig);
end
figure(figData.scatterHandle);
subplot(1,maxSubplots,subplotNumber)
if whichCell > 0;
set(gca,'fontsize',18);
if shiftPressed
plot(Cells(whichCell).correlatedResponse*2.5,Cells(whichCell).halfmatchedResponse*2.5,'o k',...
'markersize',4,'markerfacecolor','b');
xlabel('Correlated response','fontsize',18);
ylabel('Halfmatched response','fontsize',18);
%b = Cells(whichCell).regHm(2); m = Cells(whichCell).regHm(3);
[r,b,m] = regression2(Cells(whichCell).halfmatchedResponse*2.5,Cells(whichCell).correlatedResponse*2.5);
corrMin = min(Cells(whichCell).correlatedResponse)*2.5; corrMax = max(Cells(whichCell).correlatedResponse)*2.5;
delta = corrMax*0.25; corrMin = corrMin-delta; corrMax = corrMax+delta;
line([corrMin,corrMax],[m+corrMin*b,m+corrMax*b],'linewidth',2,'linestyle','-','color','r');
title(['r= ', num2str(r)])
else
plot(Cells(whichCell).correlatedResponse*2.5,Cells(whichCell).anticorrelatedResponse*2.5,'o k',...
'markersize',4,'markerfacecolor','r');
xlabel('Correlated response','fontsize',18);
ylabel('Anticorrelated response','fontsize',18);
[r,b,m] = regression2(Cells(whichCell).anticorrelatedResponse*2.5,Cells(whichCell).correlatedResponse*2.5);
corrMin = min(Cells(whichCell).correlatedResponse)*2.5; corrMax = max(Cells(whichCell).correlatedResponse)*2.5;
delta = corrMax*0.25; corrMin = corrMin-delta; corrMax = corrMax+delta;
line([corrMin,corrMax],[m+corrMin*b,m+corrMax*b],'linewidth',2,'linestyle','-','color','k');
title(['r= ', num2str(r)])
end
%reg =
elseif nargin > 2
cla
else
error('Error: This shouldn''t happen...');
end
end
if nargin == 2
figure(myFig);
if subplotNumber == 1;
subplot(1,2,2);
elseif subplotNumber == 2;
subplot(1,2,1);
end
uniqueID = quickhash([Cells(whichCell).filename, num2str(Cells(whichCell).cellnumber)]);
TC_callback(myFig,evt,uniqueID);
end
figure(myFig);
end
function keydown_callback(myFig,evt)
keydown = evt.Key;
Base = getappdata(myFig,'Base');
currentType = getappdata(myFig,'type');
if strcmp(keydown,'f');
count = 0;
for dd = [1,4];
count = count+1;
currentData = Base(dd).Cells;
subplot(1,2,count);
setappdata(gca,'subplot',count);
setappdata(gca,'density',Base(dd).density);
% Check what's currently plotted and plot whatever is not
% currently on the screen
if strcmp(currentType,'slope');
plot_ACHM(currentData)
elseif strcmp(currentType,'ACHM');
plot_slopes(currentData);
end
end
elseif strcmp(keydown,'e');
errorbars_on = getappdata(myFig,'xy_errorbars');
setappdata(myFig,'xy_errorbars',~errorbars_on);
make_subplots(myFig,NaN,Base,'Correlation');
end
end
function myHash = quickhash(string);
string = double(string);
myHash = mod(sum(string(:).^2.3),2^32-1);
end
function plot_penetrations(~,~,Base);
figure(); hold on;
set(gcf,'color','white');
SubBase = Base(1);
XYs = SubBase.penetrationlist;
exptlist = SubBase.exptlist;
for j = 1:length(exptlist);
fname = exptlist{j};
monkey = fname(9:11);
session = fname(18:24);
% Find how many cells come from that session:
count = 0;
dws = [];
for c = 1:length(SubBase.Cells);
currentFilename = SubBase.Cells(c).filename;
if strcmp(currentFilename(18:24),session);
count = count + 1;
dws = [dws,SubBase.Cells(c).dw];
end
end
dws(dws==1) = 0.15;
if strcmp(monkey,'jbe'); % colour coded by monkey
col = 'red';
else
col = 'blue';
end
XY = XYs(:,j);
plot(XY(1),XY(2),'k o','markerfacecolor',col,'markersize',5*exp(mean(dws)*4));
text(XY(1)-0.1,XY(2)+0.1,[session, ' (',num2str(count),')']);
end
end
function show_stats(myFig,evt,Base);
regHm5 = cat(1,Base(1).Cells.regHm);
regHm24 = cat(1,Base(length(Base)).Cells.regHm);
[Hr5,Pr5,CIr5,Statsr5] = ttest(regHm5(:,1),0);
[Hm5,Pm5,CIm5,Statsm5] = ttest(regHm5(:,2),0);
[Hr24,Pr24,CIr24,Statsr24] = ttest(regHm24(:,1),0);
[Hm24,Pm24,CIm24,Statsm24] = ttest(regHm24(:,2),0);
% Do this for each monkey separately
lem_idx = zeros(1,length(Base(1).Cells));
for j = 1:length(Base(1).Cells);
currentCell = Base(1).Cells(j);
lem_idx(j) = any(strfind(currentCell.filename,'lem'));
end
lem_idx = logical(lem_idx);
jbe_idx = ~lem_idx;
[~,Pm5_lem,CIm5_lem,Statsm5_lem] = ttest(regHm5(lem_idx,2),0);
[~,Pm24_lem,CIm24_lem,Statsm24_lem] = ttest(regHm24(lem_idx,2),0);
[~,Pm5_jbe,CIm5_jbe,Statsm5_jbe] = ttest(regHm5(jbe_idx,2),0);
[~,Pm24_jbe,CIm24_jbe,Statsm24_jbe] = ttest(regHm24(jbe_idx,2),0);
[~,Pm5v24,CIm5v24,Statsm5v24] = ttest(regHm5(:,2),regHm24(:,2));
[~,Pm5v24_jbe,CIm5v24_jbe,Statsm5v24_jbe] = ttest(regHm5(jbe_idx,2),regHm24(jbe_idx,2));
[~,Pm5v24_lem,CIm5v24_lem,Statsm5v24_lem] = ttest(regHm5(lem_idx,2),regHm24(lem_idx,2));
figure();
xlim([0,1]);
ylim([0,1]);
set(gca,'visible','off')
x = -0.1;
% 5% density
fs = 13;
text(x,1.0,sprintf(['one-sample t-tests testing whether slopes and \ncorrelation coefficients', ...
' are drawn from sample with mean 0']));
y1 = 0.9;
dy=0.04;
text(x,y1,'5% density','fontsize',16);
text(x,y1-dy,sprintf('r: t(%i)=%.2f, P=%.2d [95%% CIs: (%.2f, %.2f)]',Statsr5.df,Statsr5.tstat,Pr5,CIr5(1),CIr5(2)),'fontsize',fs)
text(x,y1-dy*2,sprintf('slope: t(%i)=%.2f, P=%.2d [95%% CIs: (%.2f, %.2f)]',Statsm5.df,Statsm5.tstat,Pm5,CIm5(1),CIm5(2)),'fontsize',fs);
y2 = y1-dy*3.5;
text(x,y2,'By monkey:','fontsize',14);
text(x,y2-dy,sprintf('lem slope: t(%i)=%.2f, P=%.2d [95%% CIs: (%.2f, %.2f)]',Statsm5_lem.df,Statsm5_lem.tstat,Pm5_lem,CIm5_lem(1),CIm5_lem(2)),'fontsize',fs);
text(x,y2-dy*2,sprintf('jbe slope: t(%i)=%.2f, P=%.2d [95%% CIs: (%.2f, %.2f)]',Statsm5_jbe.df,Statsm5_jbe.tstat,Pm5_jbe,CIm5_jbe(1),CIm5_jbe(2)),'fontsize',fs);
y3 = y2-dy*5;
% 5% density
text(x,y3,'24% density','fontsize',16);
text(x,y3-dy,sprintf('r: t(%i)=%.2f, P=%.2d [95%% CIs: (%.2f, %.2f)]',Statsr24.df,Statsr24.tstat,Pr24,CIr24(1),CIr24(2)),'fontsize',fs)
text(x,y3-dy*2,sprintf('slope: t(%i)=%.2f, P=%.2d [95%% CIs: (%.2f, %.2f)]',Statsm24.df,Statsm24.tstat,Pm24,CIm24(1),CIm24(2)),'fontsize',fs);
y4 = y3-dy*3.5;
text(x,y4,'By monkey:','fontsize',14);
text(x,y4-dy,sprintf('lem slope: t(%i)=%.2f, P=%.2d [95%% CIs: (%.2f, %.2f)]',Statsm24_lem.df,Statsm24_lem.tstat,Pm24_lem,CIm24_lem(1),CIm24_lem(2)),'fontsize',fs);
text(x,y4-dy*2,sprintf('jbe slope: t(%i)=%.2f, P=%.2d [95%% CIs: (%.2f, %.2f)]',Statsm24_jbe.df,Statsm24_jbe.tstat,Pm24_jbe,CIm24_jbe(1),CIm24_jbe(2)),'fontsize',fs);
y5 = y4-dy*5;
text(x,y5,'5%-24% slope comparisons','fontsize',16);