SVMCrossVal.git

@@ -21,8 +21,7 @@ timeline = header.timeline;

 PLOT_METHOD       = SVMCROSSVAL_CROSSVAL_METHOD_DEF.svmcrossval;

 PLOT_METHOD       = SVMCROSSVAL_CROSSVAL_METHOD_DEF.classPerformance;

-%         CROSSVAL_METHOD_DEF = inputStruct.CROSSVAL_METHOD_DEF;

-

+PLOT_METHOD       = 'x-subject-val';

     f = figure;

     subplot(2,1,1);

@@ -71,6 +70,17 @@ timeline = header.timeline;

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

+        case 'x-subject-val'

+            nSubjects = size(decodePerformance,2);

+            for c = 1:nSubjects

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

+            end

+

+            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

@@ -1,4 +1,4 @@

-function decodePerformance = svm_crossval(svmlabel,svmdata,svmopts)

+function decodePerformance = svm_class_performance(svmlabel,svmdata,svmopts)

 addpath 'libsvm-mat-2.88-1';

 svmmodel = svmtrain(svmlabel,svmdata,svmopts);

@@ -66,87 +66,6 @@ DEFAULT.wd  = fullfile('d:','Analyze','Choice','24pilot');

     assignin('base','model',model);

 end

-function model = mcb_cd(src,evnt,model)

-disp('CD');

-directory_name = uigetdir(model.baseDir,'Select Study Base Directory ...');

-model.baseDir = directory_name;

-model = scanDirs(model);

-end

-

-function mcb_save(src,evnt,model)

-disp('SAVE');

-baseDir  = model.baseDir;

-timeLine = getTimeLineParams(model);

-classDefString = getClassDefString(model);

-coordDefString = getCoordDefString(model);

-

-[file path] = uiputfile('*.mat','Save current Params ...',model.baseDir);

-save( fullfile(path,file),'baseDir','timeLine','classDefString','coordDefString') ;

-end

-

-function model = mcb_load(src,evnt,model)

-disp('LOAD');

-[file path] = uigetfile('*.mat','Load Params ...',model.baseDir);

-l = load(fullfile(path,file));

-% assignin('base','l',l);

-model = setTimeLineParams(model,l.timeLine);

-model = setClassDefString(model,l.classDefString);

-model = setCoordDefString(model,l.coordDefString);

-model.baseDir = l.baseDir;

-model = scanDirs(model);

-

-end

-

-function model = createSecondStepPanel(model,parent,DEFAULT,basecolor)

-    

-pSVM = uipanel(parent,'Units','normalized','Position',[0 0.0 0.5 1]);

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

-    set(pSVM,'BackgroundColor',basecolor);

-

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

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

-    

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

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

-    

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

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

-    set(pSOM,'BackgroundColor',basecolor);

-

-    model.txtSOMopts = createTextField(pSOM,[0 0.75 1 0.25],'4x3 rect');

-    set(model.txtSOMopts,'HorizontalAlignment','left');

-        set(model.txtSOMopts,'Enable','off');

-

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

-        set(model.txtSOMnfold,'Enable','off');

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

-

-% buttons

-    btnRunSVM = uicontrol(pSVM,'String','run SVM Crossvalidation',...

-        'Units','normalized',...

-        'Position',[0 0.25 1 0.25]);

-    set(btnRunSVM,'Callback',{@cbRunDecode,model,'SVM'}); % set here, because of model.

-    set(btnRunSVM,'Enable','on');

-    

-    btnRunXSVM = uicontrol(pSVM,'String','run SVM X-Subject validation',...

-        'Units','normalized',...

-        'Position',[0 0.0 1 0.25]);

-    set(btnRunXSVM,'Callback',{@cbRunDecode,model,'XSVM'}); % set here, because of model.

-    set(btnRunXSVM,'Enable','on');

-    

-    btnRunSOM = uicontrol(pSOM,'String','run SOM Crossvalidation',...

-        'Units','normalized',...

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

-    set(btnRunSOM,'Callback',{@cbRunDecode,model,'SOM'}); % set here, because of model.

-    set(btnRunSOM,'Enable','off');

-

-    btnRunXSOM = uicontrol(pSOM,'String','run SOM X-Subject validation',...

-        'Units','normalized',...

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

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

-    set(btnRunXSOM,'Enable','off');

-end

-

 function model = createFirstStepPanel(model,parent,DEFAULT)

     main_grid = cell(2,4);

@@ -317,6 +236,58 @@ function model = createFirstStepPanel(model,parent,DEFAULT)

         set(btnRunButton3,'Enable','on');

 end

+function model = createSecondStepPanel(model,parent,DEFAULT,basecolor)

+    

+pSVM = uipanel(parent,'Units','normalized','Position',[0 0.0 0.5 1]);

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

+    set(pSVM,'BackgroundColor',basecolor);

+

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

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

+    

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

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

+    

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

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

+    set(pSOM,'BackgroundColor',basecolor);

+

+    model.txtSOMopts = createTextField(pSOM,[0 0.75 1 0.25],'4x3 rect');

+    set(model.txtSOMopts,'HorizontalAlignment','left');

+        set(model.txtSOMopts,'Enable','off');

+

+    model.txtSOMnfold = createTextField(pSOM,[0.0 0.50 0.5 0.25],DEFAULT.svmnfold);

+        set(model.txtSOMnfold,'Enable','off');

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

+

+% buttons

+    btnRunSVM = uicontrol(pSVM,'String','run SVM Crossvalidation',...

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

+        'Position',[0 0.25 1 0.25]);

+    set(btnRunSVM,'Callback',{@cbRunDecode,model,'SVM'}); % set here, because of model.

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

+    

+    btnRunXSVM = uicontrol(pSVM,'String','run SVM X-Subject validation',...

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

+        'Position',[0 0.0 1 0.25]);

+    set(btnRunXSVM,'Callback',{@cbRunDecode,model,'XSVM'}); % set here, because of model.

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

+    

+    btnRunSOM = uicontrol(pSOM,'String','run SOM Crossvalidation',...

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

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

+    set(btnRunSOM,'Callback',{@cbRunDecode,model,'SOM'}); % set here, because of model.

+    set(btnRunSOM,'Enable','off');

+

+    btnRunXSOM = uicontrol(pSOM,'String','run SOM X-Subject validation',...

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

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

+    set(btnRunXSOM,'Callback',{@cbRunDecode,model,'XSOM'}); % set here, because of model.

+    set(btnRunXSOM,'Enable','off');

+end

+

+

+

 function cbRunPreprocessing(src,evnt,model,task)

 main(model,'pre',task);

 end

@@ -325,6 +296,37 @@ function cbRunDecode(src,evnt,model,task)

 main(model,'decode',task);

 end

+function model = mcb_cd(src,evnt,model)

+disp('CD');

+directory_name = uigetdir(model.baseDir,'Select Study Base Directory ...');

+model.baseDir = directory_name;

+model = scanDirs(model);

+end

+

+function mcb_save(src,evnt,model)

+disp('SAVE');

+baseDir  = model.baseDir;

+timeLine = getTimeLineParams(model);

+classDefString = getClassDefString(model);

+coordDefString = getCoordDefString(model);

+

+[file path] = uiputfile('*.mat','Save current Params ...',model.baseDir);

+save( fullfile(path,file),'baseDir','timeLine','classDefString','coordDefString') ;

+end

+

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

+disp('LOAD');

+[file path] = uigetfile('*.mat','Load Params ...',model.baseDir);

+l = load(fullfile(path,file));

+% assignin('base','l',l);

+model = setTimeLineParams(model,l.timeLine);

+model = setClassDefString(model,l.classDefString);

+model = setCoordDefString(model,l.coordDefString);

+model.baseDir = l.baseDir;

+model = scanDirs(model);

+

+end

+

 function label = createLabel(parent,  pos, labelText)

     label = uicontrol(parent,'Style','text','Units','normalized','String',labelText,'Position',pos);

     set(label,'HorizontalAlignment','left');

@@ -1,9 +0,0 @@

-function decode = xsvm_single_crossval()

-

-%for each subject in test

-% append svmdata and svm label

-% train svm

-% test with testsubject

-%end

-

-end

\ No newline at end of file

@@ -1,8 +1,12 @@

 %% subject loop

 function decode = xsvm_subject_loop(header,subjectdata,svmopts)

+addpath 'libsvm-mat-2.88-1';

+

 nSubjects = numel(subjectdata);

+RANDOMIZE_DATAPOINTS = 0;

+

 decode = struct;

 decode.decodePerformance = [];

 decode.rawTimeCourse     = [];

@@ -11,6 +15,7 @@ disp(sprintf('computinig additional datastructs for %u subjects',nSubjects));

 timeline = header.timeline;

+% TimePointMatrix

 for subjectDataID = 1:nSubjects

     currentSubject = subjectdata{subjectDataID};

     timePointArgs.pst           = currentSubject.pst;

@@ -18,16 +23,18 @@ for subjectDataID = 1:nSubjects

     timePointArgs.eventList     = header.classDef.eventMatrix;

     timePointMatrix{subjectDataID} = buildTimePointMatrix(timeline,timePointArgs);

+    

+    decode.rawTimeCourse = [decode.rawTimeCourse currentSubject.pst];

 end

+% timeframe x-subject validation

 timeLineStart   = timeline.frameShiftStart;

 timeLineEnd     = timeline.frameShiftEnd;

-addpath 'libsvm-mat-2.88-1';

-

 display(sprintf('%u -fold cross validation for %u timeslices.\n',nSubjects,size(1:timeLineEnd-timeLineStart+1,2)));

-disp(sprintf('Press ANY-Key to continue.\n Use Retrun if your Keyboard lacks the ANY-Key.'));

-pause

+% disp(sprintf('Press ANY-Key to continue.\n Use Retrun if your Keyboard lacks the ANY-Key.'));

+% pause

+

 for timeIndex = 1:timeLineEnd-timeLineStart+1

     cross_value = [];

     for validationSubjectID = 1:nSubjects

@@ -46,8 +53,11 @@ for timeIndex = 1:timeLineEnd-timeLineStart+1

             end

         end

-%         display(sprintf('Time %u: validation subject: %u, validation set size %g, training set size %g with %u subjects',...

-%             timeIndex, validationSubjectID, numel(svm_validation_label), numel(svm_train_label),nSubjects-1));

+        if RANDOMIZE_DATAPOINTS

+            rndindex  = randperm(length(svm_train_label));

+            svm_train_data   = svm_train_data(rndindex,:);

+            svm_train_label  = svm_train_label(rndindex);

+        end

         svmmodel = svmtrain(svm_train_label,svm_train_data,svmopts);

@@ -55,26 +65,7 @@ for timeIndex = 1:timeLineEnd-timeLineStart+1

         cross_value = [cross_value accuracy(1)];

     end

-    decode.decodePerformance = [decode.decodePerformance mean(cross_value)];

-%     decode.rawTimeCourse = [decode.rawTimeCourse cross_value];

-    

-%         decode.(namehelper)         = calculateDecodePerformance(header,currentSubject,svmopts);

-% 

-%         display('... done');

-%         display('restoring warnings');

-%         warning(warning_state);

-% 

-%         decode.decodePerformance    = [decode.decodePerformance decode.(namehelper).decodePerformance];

-%         decode.rawTimeCourse        = [decode.rawTimeCourse decode.(namehelper).rawTimeCourse];

-

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

-

-        %         if RANDOMIZE_DATAPOINTS

-        %         rndindex  = randperm(length(svmlabel));

-        %         svmdata   = svmdata(rndindex,:);

-        %         svmlabel  = svmlabel(rndindex);

-        %         end

-

+    decode.decodePerformance = [decode.decodePerformance; cross_value];

 end

 end