SVMCrossVal.git

@@ -155,7 +155,7 @@ function pst = calculatePST(timeline,pstopts,data)

     %%%%%%%%%%% new 090109 Axel: "Normalization" for SVM

-    norm4SVM='minmax'; %Normalization method for SVM

+    norm4SVM='mean'; %Normalization method for SVM

     disp(['normalization: ' norm4SVM]);   

     % none - no normalization

     % mean - mean normalization (meanPSTH max at .5, baseline at -.5]

@@ -85,11 +85,13 @@ switch task

         disp('SVM');

         svmopts    = getSvmArgs(model,1);

         decode = calculateMultiSubjectDecodePerformance(header,data,svmopts);

+        decode.header = header;

         assignin('base','decode',decode);

     case 'XSVM'

         disp('XSVM')

         svmopts  = getSvmArgs(model,0);

         decode = xsvm_subject_loop(header,data,svmopts);

+        decode.header = header;

         assignin('base','decode',decode);

     case 'SOM'

         disp('not implemented')

@@ -104,11 +106,11 @@ end

 end

 function decode_plot(model,type)

-switch type

-    case 'SIMPLE'

+decode = evalin('base','decode');

+preprocessed = evalin('base','preprocessedData');

+plotDecodePerformance(type,decode,preprocessed.subjectdata);

 end

-end

@@ -1,50 +1,31 @@

-function plotDecodePerformance(header,decode,subjectData)

+function plotDecodePerformance(type,decode,subjectData)

-global SVMCROSSVAL_CROSSVAL_METHOD_DEF;

-

-PSTH_AXIS_MIN = -2;

-PSTH_AXIS_MAX = 2;

+type

+header = decode.header;

 timeline = header.timeline;

+frameshift = header.frameShift;

 psthStart         = timeline.psthStart;

 psthEnd           = timeline.psthEnd;

-frameStart        = timeline.frameShiftStart;

-frameEnd          = timeline.frameShiftEnd;

+frameStart        = frameshift.frameShiftStart;

+frameEnd          = frameshift.frameShiftEnd;

 nClasses          = numel(header.classDef.labelCells);

 decodePerformance = decode.decodePerformance;

 psth              = decode.rawTimeCourse;

 SubjectID         = subjectData;

-smoothed          = 'yes';

+nSubjects         = size(SubjectID,2);

-PLOT_METHOD       = SVMCROSSVAL_CROSSVAL_METHOD_DEF.svmcrossval;

-PLOT_METHOD       = SVMCROSSVAL_CROSSVAL_METHOD_DEF.classPerformance;

-PLOT_METHOD       = 'x-subject-val';

     f = figure;

     subplot(2,1,1);

-    hold on;

-    if (size(psth) > 0)

-      for voxel = 1:size(psth,2)

-          for label = 1:size(psth{voxel},2)

-              psthData = [];

-              for timepoint = 1:size(psth{voxel}{label},2)

-                  psthData = nanmean(psth{voxel}{label});

-              end

-              plot(psthStart:psthEnd,psthData,[colorChooser(voxel), lineStyleChooser(label)]);

-          end

-      end

-    end

-    axis([psthStart psthEnd PSTH_AXIS_MIN PSTH_AXIS_MAX])

-    xlabel('time [sec]');

-    ylabel('fMRI-signal change [%]');

-    hold off

+        plotPSTH(psth,psthStart,psthEnd);

+    % plot performance timeline

     subplot(2,1,2)    

     hold on;

-    

     chanceLevel = 100/nClasses;

     goodPredictionLevel = chanceLevel*1.5;

     plot([psthStart psthEnd],[chanceLevel chanceLevel],'k:');

@@ -53,39 +34,25 @@ PLOT_METHOD       = 'x-subject-val';

     xlabel('time [sec]');

     ylabel('decode performance [%]');

-    

-    

-    switch PLOT_METHOD

-        case SVMCROSSVAL_CROSSVAL_METHOD_DEF.svmcrossval

-            plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b','LineWidth',2);

-

-            se = myStdErr(decodePerformance,2);

-            plot(frameStart:frameEnd, mean(decodePerformance,2)+se ,'b:');

-            plot(frameStart:frameEnd, mean(decodePerformance,2)-se ,'b:');

-        case SVMCROSSVAL_CROSSVAL_METHOD_DEF.classPerformance

-            for c = 1:size(decodePerformance,2)

-                plot(frameStart:frameEnd, decodePerformance(:,c) ,[colorChooser(mod(c,nClasses)+3) '-']);

-            end

-

-            plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b','LineWidth',2);

-            

+    switch type

+        case 'simple'

+            plotDecodePerformanceWithSE(frameStart,frameEnd,decodePerformance)

+        case 'class performance'

+            plotClassPerformance(frameStart,frameEnd,decodePerformance,nClasses)

         case 'x-subject-val'

-            nSubjects = size(decodePerformance,2);

             for c = 1:nSubjects

                 plot(frameStart:frameEnd, decodePerformance(:,c) ,[colorChooser(mod(c,nSubjects)+3) '-']);

             end

+            plotDecodePerformanceWithSE(frameStart,frameEnd,decodePerformance)

+    end

+    hold off;

-            plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b','LineWidth',2);

-            se = myStdErr(decodePerformance,2);

-            plot(frameStart:frameEnd, mean(decodePerformance,2)+se ,'b:');

-            plot(frameStart:frameEnd, mean(decodePerformance,2)-se ,'b:');

+%     setTitle(f,header,decode,subjectData);

 end

+function setTitle(f,header,decode,subjectData)

-    hold off;

-    

-    nSubjects = size(SubjectID,2);

     nVoxelPerSubject = size(psth,2)/size(SubjectID,2);

     if strcmp(smoothed,'yes')

@@ -104,9 +71,45 @@ PLOT_METHOD       = 'x-subject-val';

     set(f,'Name',title);

     display(sprintf('%s',title));

+end

+

+function plotClassPerformance(frameStart,frameEnd,decodePerformance,nClasses)

+for c = 1:size(decodePerformance,2)

+    plot(frameStart:frameEnd, decodePerformance(:,c) ,[colorChooser(mod(c,nClasses)+3) '-']);

+end

+plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b','LineWidth',2);

+end

+

+function plotDecodePerformanceWithSE(frameStart,frameEnd,decodePerformance)

+plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b','LineWidth',2);

+

+se = myStdErr(decodePerformance,2);

+plot(frameStart:frameEnd, mean(decodePerformance,2)+se ,'b:');

+plot(frameStart:frameEnd, mean(decodePerformance,2)-se ,'b:');

+end

+function plotPSTH(psth,psthStart,psthEnd)

+PSTH_AXIS_MIN = -2;

+PSTH_AXIS_MAX = 2;

+

+    hold on;

+    if (size(psth) > 0)

+      for voxel = 1:size(psth,2)

+          for label = 1:size(psth{voxel},2)

+              psthData = [];

+              for timepoint = 1:size(psth{voxel}{label},2)

+                  psthData = nanmean(psth{voxel}{label});

+              end

+              plot(psthStart:psthEnd,psthData,[colorChooser(voxel), lineStyleChooser(label)]);

+          end

+      end

+    end

+    axis([psthStart psthEnd PSTH_AXIS_MIN PSTH_AXIS_MAX])

+    xlabel('time [sec]');

+    ylabel('fMRI-signal change [%]');

+    hold off

 end

@@ -352,16 +352,28 @@ pSOM = uipanel(parent,'Units','normalized','Position',[0.5 0.4 0.5 0.4]);

 end

 function model = createVisualStepPanel(model,parent,DEFAULT)

-    pButtonPane = uipanel(parent,'Units','normalized','Position',[0.0 0.5 1 0.5]);

+    pButtonPane = uipanel(parent,'Units','normalized','Position',[0 0.5 1 0.5]);

 %     set(pButtonPane,'Title','Plot');

     set(pButtonPane,'BackgroundColor','w');

-    btnPlot01 = uicontrol(pButtonPane,'String','plot BBBB',...

+    btnPlot01 = uicontrol(pButtonPane,'String','plot performance and SE',...

         'Units','normalized',...

-        'Position',[0.0 0.0 1 0.25]);

-    set(btnPlot01,'Callback',{@cbPlot,model,'XSOM'}); % set here, because of model.

+        'Position',[0.0 0.0 0.5 0.25]);

+    set(btnPlot01,'Callback',{@cbPlot,model,'simple'});

     set(btnPlot01,'Enable','on');

+    btnPlot02 = uicontrol(pButtonPane,'String','plot subject performance and mean with SE',...

+        'Units','normalized',...

+        'Position',[0.5 0.0 0.5 0.25]);

+    set(btnPlot02,'Callback',{@cbPlot,model,'x-subject-val'});

+    set(btnPlot02,'Enable','on');

+

+%     btnPlot03 = uicontrol(pButtonPane,'String','plot class performance and mean',...

+%         'Units','normalized',...

+%         'Position',[0.0 0.5 0.5 0.25]);

+%     set(btnPlot03,'Callback',{@cbPlot,model,'class performance'}); 

+%     set(btnPlot03,'Enable','on');

+    

 end

@@ -390,7 +402,6 @@ main(model,'decode',task);

 end

 function cbPlot(src,evnt,model,type)

-display('Not Implemented');

 main(model,'plot',type);

 end