SVMCrossVal.git

@@ -1,6 +1,6 @@

 function outputStruct = calculateDecodePerformance(header,subjectStruct,svmopts)

 outputStruct = struct;

-RANDOMIZE_DATAPOINTS = 1;

+RANDOMIZE_DATAPOINTS = header.svmrnd;

 timeline = header.timeline;

 timeline.frameShiftStart = header.frameShift.frameShiftStart;

@@ -6,8 +6,7 @@ decode.decodePerformance = [];

 decode.rawTimeCourse     = [];

 nSubjects = numel(subjectdata);

-% disp(sprintf('we have %g subjects. Press ANY-Key to continue.\n Use Retrun if your Keyboard lacks the ANY-Key.',numel(subjectdata)));

-% pause

+

 disp(sprintf('batch processing %g subjects',nSubjects));

 for subjectDataID = 1:nSubjects

@@ -85,6 +85,7 @@ switch task

     case 'SVM'

         disp('SVM');

         svmopts    = getSvmArgs(model,1);

+        header.svmrnd = getSvmRnd(model);

         decode = calculateMultiSubjectDecodePerformance(header,data,svmopts);

         decode.header = header;

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

@@ -13,8 +13,10 @@ DEFAULT.classdefstring  = 'left,\t[9,11,13]\nright,\t[10,12,14]';

 DEFAULT.voxelstring     = 'SPL l + [ 0, 0, 0] \nSPL r + [ 0, 0, 0]\n';

 DEFAULT.svmoptstring    = '-s 0 -t 0 -c 1';

 DEFAULT.svmnfold        = '6';

+DEFAULT.svmrnd          = 1;

 DEFAULT.searchlightradius = 0;

+

 DEFAULT.wd  = fullfile('d:','Analyze','Choice','24pilot');

 %  Initialize and hide the GUI as it is being constructed.

@@ -307,12 +309,18 @@ pSVM = uipanel(parent,'Units','normalized','Position',[0 0.4 0.5 0.4]);

     set(pSVM,'Title','SVM Classification');

     set(pSVM,'BackgroundColor',basecolor);

-    model.txtSVMopts = createTextField(pSVM,[0 0.75 1 0.25],DEFAULT.svmoptstring);

+    model.txtSVMopts = createTextField(pSVM,[0 0.83 1 0.16],DEFAULT.svmoptstring);

     set(model.txtSVMopts,'HorizontalAlignment','left');

-    model.txtSVMnfold = createTextField(pSVM,[0.0 0.50 0.5 0.25],DEFAULT.svmnfold);

+    model.txtSVMnfold = createTextField(pSVM,[0.0 0.66 0.5 0.16],DEFAULT.svmnfold);

     createLabel(pSVM,[0.5 0.50 0.5 0.25 ],'-Fold CrossVal');

+    model.chkSVMrnd = uicontrol(pSVM,'Style','checkbox','Units','normalized','Position',[0.1 0.50 1 0.16]);

+    set(model.chkSVMrnd,'String','Randomize Datapoints');

+    set(model.chkSVMrnd,'BackgroundColor','w');

+    set(model.chkSVMrnd,'Value',DEFAULT.svmrnd);

+    

+    

 pSOM = uipanel(parent,'Units','normalized','Position',[0.5 0.4 0.5 0.4]);

     set(pSOM,'Title','SOM Classification');

     set(pSOM,'BackgroundColor',basecolor);

@@ -8,7 +8,7 @@ if(nSubjects < 2)

     error('SVMCrossVal:xsvmSubjectLoop:tooFewSubjects','You need at least 2 Subjects in this Across-Subject analysis!');

 end

-RANDOMIZE_DATAPOINTS = 0;

+RANDOMIZE_DATAPOINTS = 1;

 decode = struct;

 decode.decodePerformance = [];