SVMCrossVal.git

@@ -16,14 +16,13 @@ SubjectID         = subjectData;

 nSubjects         = size(SubjectID,2);

+nTrials           = getNTrials(psth);

     f = figure;

     hold on;

     chanceLevel = 100/nClasses;

-    goodPredictionLevel = chanceLevel*1.5;

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

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

+

     axis([psthStart psthEnd 0 100])

     xlabel('time [sec]');

     ylabel('decode performance [%]');

@@ -41,12 +40,40 @@ nSubjects         = size(SubjectID,2);

             end

             plotDecodePerformanceWithSE(frameStart,frameEnd,decodePerformance)

     end

+    

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

+

+    plotBinConfidenceIntervall(psthStart,psthEnd,nTrials,0.05,chanceLevel/100,'r');

+    plotBinConfidenceIntervall(psthStart,psthEnd,nTrials,0.01,chanceLevel/100,'g');

+    

     hold off;

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

 end

+function plotBinConfidenceIntervall(pStart,pEnd,nTrials,alpha,limit,color)

+    [pLevel Z] = rev_ki_bin(nTrials,alpha,limit);

+    [lower upper proz] = ki_bin(Z,nTrials,alpha);

+

+    plot([pStart pEnd],[pLevel*100 pLevel*100],[color ':']);

+

+    plot([pStart pEnd],[lower*100 lower*100],[color '-.']);

+    plot([pStart pEnd],[upper*100 upper*100],[color '-.']);

+end

+

+function n = getNTrials(psth)

+nSubjects = size(psth,2);

+

+n = 0;

+for ns = 1:nSubjects

+    nClasses = size(psth{ns},2);

+    for nc = 1:nClasses

+        n = n + size(psth{ns}{nc},1);

+    end

+end

+end

+

 function plotClassPerformance(frameStart,frameEnd,decodePerformance,nClasses)

 for c = 1:size(decodePerformance,2)

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

@@ -76,6 +103,7 @@ PSTH_AXIS_MAX = 2;

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

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

               end

+              PSTH_AXIS_MAX = max(PSTH_AXIS_MAX,nanmax(psthData));

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

           end

       end

@@ -71,7 +71,11 @@ function ui_main(varargin)

     % MENUS

     savemenu = uimenu(frame,'Label','Save ...','Enable','on');

-        uimenu(savemenu,'Label','Save All','Callback',{@mcb_save,model},'Enable','on');

+        uimenu(savemenu,'Label','Save Parameter','Callback',{@mcb_save,'PARAMS',model},'Enable','on');

+        uimenu(savemenu,'Label','Save ImageProcesseding Data','Callback',{@mcb_save,'IMAGEPROCESSING',model},'Enable','on');

+        uimenu(savemenu,'Label','Load ImageProcesseding Data','Callback',{@mcb_load,'IMAGEPROCESSING',model},'Enable','on');

+        uimenu(savemenu,'Label','Save Decode Data','Callback',{@mcb_save,'DECODE',model},'Enable','on');

+        uimenu(savemenu,'Label','Load Decode Data','Callback',{@mcb_load,'DECODE',model},'Enable','on');

     studySelectMenu = uimenu(frame,'Label','Study ...','Enable','on');

         uimenu(studySelectMenu,'Label','*new Study*','Callback',{@mcb_new_study,studySelectMenu,model});

@@ -473,9 +477,47 @@ end

 %%%%%%%%%% menu callbacks

-function mcb_save(src,evnt,model)

+function mcb_save(src,evnt,token,model)

+switch token

+    case 'PARAMS'

         studyID = get(model.txtStudyID,'String');

         saveStudy(studyID,model);

+    case 'IMAGEPROCESSING'

+        disp('save img data..');

+        [FileName,PathName,FilterIndex] = uiputfile('*.mat','Save ImageProcessing Data') ;

+        if(~strcmp(FileName,''))

+            evalin('base', sprintf('save(''%s'',''%s'')',fullfile(PathName,FileName),'preprocessedData'));

+            disp('saved');

+        end

+%         [FileName,PathName,FilterIndex] = uigetfile('*.mat','Load ImageProcessing Data') 

+%         evalin('base', sprintf('load(%s,%s)',fullfile(PathName,FileName),'preprocessedData'));

+    case 'DECODE'

+        disp('save decode data..');

+        [FileName,PathName,FilterIndex] = uiputfile('*.mat','Save Decode Data') ;

+        if(~strcmp(FileName,''))

+            evalin('base', sprintf('save(''%s'',''%s'')',fullfile(PathName,FileName),'decode'));

+            disp('saved');

+        end

+end

+end

+

+function mcb_load(src,evnt,token,model)

+switch token

+    case 'IMAGEPROCESSING'

+        disp('load img data..');

+        [FileName,PathName,FilterIndex] = uigetfile('*.mat','Load ImageProcessing Data') ;

+        if(~strcmp(FileName,''))

+            evalin('base', sprintf('load(''%s'',''%s'')',fullfile(PathName,FileName),'preprocessedData'));

+            disp('done');

+        end

+    case 'DECODE'

+        disp('load decode data..');

+        [FileName,PathName,FilterIndex] = uigetfile('*.mat','Load Decode Data') ;

+        if(~strcmp(FileName,''))

+            evalin('base', sprintf('load(''%s'',''%s'')',fullfile(PathName,FileName),'decode'));

+            disp('done');

+        end

+end

 end

 function mcb_update_subjects(src,evnt,model)