SVMCrossVal.git

@@ -1,36 +1,4 @@

-% filenameList as in SPM.xY.VY

-% voxelList in [x y z], 1 coordinate per row

-

 function extr = calculateImageData(filenameList, voxelList)

-TRANSFORM_METHOD = 'single';

-%function extr = calculateImageData(voxelList,des,smoothed)

-% global USE_DRIVE_CHECK_HACK;

-

-% dtype='PSTH';

-

-% switch dtype 

-%     case 'PSTH'

-%         V=des.xY.VY;

-%     case 'betas'

-%         V=des.Vbeta;

-% end;

-

-% if USE_DRIVE_CHECK_HACK

-% if V(1).fname(1)~='D'

-%      for z=1:length(V) % Change Drive Letter - HACK!

-%       	V(z).fname(1) = 'D';

-%      end; 

-% end

-% end

-

-% if (~smoothed)

-%   for z=1:length(V) % Change smoothed Filename - HACK!

-%       % D:....SUBJECTID\session\swfanders...

-%       % D:....SUBJECTID\session\wfanders...

-%       tmp = findstr(filesep,V(z).fname);

-%       V(z).fname = strcat(V(z).fname(1:tmp(end)),V(z).fname(tmp(end)+2:end));

-%   end;

-% end

 V = filenameList;

@@ -39,59 +7,31 @@ nVoxel = size(vox,1);

 nImage = numel(V);

 for kImage=1:nImage

-% 	extr(kImage) = struct(...

-%         'dat',  ...

-%         'val',   repmat(NaN, [1 nVoxel]),...

-% 		'mean',  repmat(NaN, [1 nVoxel]),...

-% 		'sum',   repmat(NaN, [1 nVoxel]),...

-% 		'nvx',   repmat(NaN, [1 nVoxel]),...

-% 		'posmm', repmat(NaN, [3 nVoxel]),...

-% 		'posvx', repmat(NaN, [3 nVoxel]));

-

-    switch TRANSFORM_METHOD

-        case 'single'

     roicenter = round(inv(V(kImage).mat)*[vox, ones(nVoxel,1)]');

     x = roicenter(1,:);

     y = roicenter(2,:);

     z = roicenter(3,:);

-        case 'image'

-             x = []; y = []; z = [];

-            for iRoiFile = 1:nRoiFiles 

-                [x1 y1] = ndgrid(1:V(k).dim(1),1:V(k).dim(2));

-                for p = 1:V(k).dim(3) % resample mask Vm(iRoiFile) in space of V(k)

-                    B = spm_matrix([0 0 -p 0 0 0 1 1 1]);

-                    M = inv(B*inv(V(k).mat)*Vm(iRoiFile).mat);

-                    msk = find(spm_slice_vol(Vm(iRoiFile),M,V(k).dim(1:2),0));

-                    if ~isempty(msk)

-                        z1 = p*ones(size(msk(:)));

-                        x = [x; x1(msk(:))];

-                        y = [y; y1(msk(:))];

-                        z = [z; z1];

-                    end;

-                end;

-            end

-    end

     for iVoxel = 1:nVoxel

-%         if rad==0

+        if rad==0

             x = roicenter(1,iVoxel);

             y = roicenter(2,iVoxel);

             z = roicenter(3,iVoxel);

-%         else

-%             tmp = spm_imatrix(V(kImage).mat);

-%             vdim = tmp(7:9);

-%             vxrad = ceil((rad*ones(1,3))./(ones(nVoxel,1)*vdim))';

-%             [x y z] = ndgrid(-vxrad(1,iVoxel):sign(vdim(1)):vxrad(1,iVoxel), ...

-%                       -vxrad(2,iVoxel):sign(vdim(2)):vxrad(2,iVoxel), ...

-%                       -vxrad(3,iVoxel):sign(vdim(3)):vxrad(3,iVoxel));

-%             sel = (x./vxrad(1,iVoxel)).^2 + (y./vxrad(2,iVoxel)).^2 + ...

-%                   (z./vxrad(3,iVoxel)).^2 <= 1;

-%             x = roicenter(1,iVoxel)+x(sel(:));

-%             y = roicenter(2,iVoxel)+y(sel(:));

-%             z = roicenter(3,iVoxel)+z(sel(:));

-%         end;

+        else

+            tmp = spm_imatrix(V(kImage).mat);

+            vdim = tmp(7:9);

+            vxrad = ceil((rad*ones(1,3))./(ones(nVoxel,1)*vdim))';

+            [x y z] = ndgrid(-vxrad(1,iVoxel):sign(vdim(1)):vxrad(1,iVoxel), ...

+                -vxrad(2,iVoxel):sign(vdim(2)):vxrad(2,iVoxel), ...

+                -vxrad(3,iVoxel):sign(vdim(3)):vxrad(3,iVoxel));

+            sel = (x./vxrad(1,iVoxel)).^2 + (y./vxrad(2,iVoxel)).^2 + ...

+                (z./vxrad(3,iVoxel)).^2 <= 1;

+            x = roicenter(1,iVoxel)+x(sel(:));

+            y = roicenter(2,iVoxel)+y(sel(:));

+            z = roicenter(3,iVoxel)+z(sel(:));

+        end;

         dat = spm_sample_vol(V(kImage), x, y, z,0);

@@ -0,0 +1,45 @@

+%% subject loop

+function decode = claculateMultiSubjectDecodePerformance(timelineParams,calculateParams,paramModel)

+

+decode = struct;

+decode.decodePerformance = [];

+decode.rawTimeCourse     = [];

+

+for subjectCell = calculateParams.subjectSelection

+    SubjectID = cell2mat(subjectCell);

+    namehelper = strcat('s',SubjectID); %Vars can not start with numbers.

+

+    display('loading SPM.mat ...');

+    spm = load(fullfile(calculateParams.PROJECT_BASE_PATH,SubjectID,calculateParams.PROJECT_RESULT_PATH));

+    display('... done.');

+

+    % per subject params..

+    subjectParams = struct;

+    

+    subjectParams.des             = spm.SPM;

+

+

+    subjectParams.voxelList       = mapVoxelList(voxelList,SubjectID);

+

+    

+    subjectParams.SubjectID       = SubjectID;

+    subjectParams.namehelper      = namehelper;

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

+

+    display(sprintf('calculating cross-validation performance time-shift for Subject %s. Please Wait. ...',SubjectID));

+    display('switching off all warnings');

+    warning_state               = warning('off','all');

+    display('calculating ...');

+    decode.(namehelper)         = calculateDecodePerformance(timelineParams,calculateParams,subjectParams);

+

+    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);

+end

+

+end

@@ -0,0 +1,19 @@

+function scoords = getSubjectCoordinates(gcoords,map)

+m = java.util.HashMap ;

+

+for i = 1:numel(map.names)

+    key = cell2mat(map.names(i));

+    val = map.coords(i,:);

+    m.put(key,val);

+end

+

+scoords = [];

+

+for c = 1:numel(gcoords)

+    key = strtrim(gcoords(c).name);

+    val = m.get(key)';

+    mod = gcoords(c).mod;

+    scoords = [scoords; val+mod];

+end

+

+end

\ No newline at end of file

@@ -5,14 +5,24 @@ disp('RUN');

 timeLine = getTimeLineParams(model);

 subjects = getSubjectCellList(model);

 classDef = parseClassDef(model);

+

+mask     = ['^' cell2mat(getImageFileMask(model)) '.*\.img$'];

 % images

 % normalization

 switch task

     case 'COORD'

         disp('COORD');

-        coordinates= 'parse me';

-        runCoordTable()

+        coordargs = struct;

+        coordargs.subjects = subjects;

+        coordargs.timeline = timeLine;

+        coordargs.basedir = model.baseDir;

+        coordargs.sessionList = 1:3;

+        coordargs.eventList = classDef.eventMatrix;

+        coordargs.coords = parseCoordinateTextField(model);

+        coordargs.mask   = mask;

+        

+        runCoordTable(coordargs)

     case 'ROI'

         disp('ROI');

@@ -20,8 +30,10 @@ switch task

         roiargs.subjects    = subjects;

         roiargs.timeline    = timeLine;

         roiargs.classes     = classDef;

-        roiargs.mask     = getImageFileMask(model);

+        roiargs.mask        = mask;

         roiargs.basedir     = model.baseDir;

+        roiargs.sessionList = 1:3;

+        roiargs.eventList   = classDef.eventMatrix;

         assignin('base','roiargs',roiargs);

@@ -1,5 +1,5 @@

-function voxelList = parseCoordinateTextField(txtFieldHandel)

-s = get(txtFieldHandel,'String');

+function voxelList = parseCoordinateTextField(model)

+s = get(model.txtVoxelDef,'String');

 rows = size(s,1);

 voxelList = [];

     for i = 1:rows 

@@ -1,51 +0,0 @@

-function voxelList = parseVoxelList(model,multisubjectid)

-        voxelList = [];

-

-        %<ROI Name>,<ROI Modifier>;

-        txt = get(model.txtVoxelDef,'String');

-        map = model.subjectMap;

-

-        switch nargin

-            case 1

-                SubjectID = getSubjectIDString(model);

-            case 2

-                SubjectID = multisubjectid;

-            otherwise

-                error('spmtoolbox:SVMCrossVal:parseVoxelList:nargin','wrong number of arguments given');

-        end

-         

-        rows  = size(txt,1);

-        

-        for i = 1:rows 

-            if all(isspace(txt(i,:)))

-                continue;

-            end

-            line = txt(i,:);

-            roi = parseROIName(line);

-            roimod = parseModifier(line);

-            voxelList = [voxelList; getCoordinate(map,SubjectID,roi)+eval(roimod)];

-        end

-end

-

-function roi = parseROIName(line)

-c = 1;

-roi = '';

-while line(c)~=','

-    roi = [roi line(c)];

-    c = c+1;

-end

-roi = strtrunc(roi);

-end

-

-function roimod = parseModifier(line)

-c = 1;

-while line(c)~=',' % skip roi

-    c=c+1;

-end

-c=c+1; % skip ','

-roimod='';

-while line(c) ~= ';'

-    roimod = [roimod line(c)];

-    c = c+1;

-end

-end

@@ -1,98 +1,53 @@

-function ppsth = runCoordTable(baseDir,subjects,timeline,coordinates,volumeFileList,classDef)

-%         paramModel = varargin{1};

+function runCoordTable(args)

     disp('run coord table')

-    disp('does not work yet.')

-    return

+    subjects = args.subjects;

+    nSubjects = size(subjects);

+    sessionlist = args.sessionList;

-        PROJECT_BASE_PATH = baseDir;

-        PROJECT_RESULT_PATH = 'results\SPM.mat';

+    for s = 1:nSubjects

+        subjectStruct{s}.dir = fullfile(args.basedir,cell2mat(subjects(s)));

+        d = load(fullfile(subjectStruct{s}.dir,'results','SPM.mat'));

+        subjectStruct{s}.des = d.SPM;

+        subjectStruct{s}.name = cell2mat(subjects(s));

+        map = load(fullfile(subjectStruct{s}.dir,'results','roi','coord_map.mat'));

+        subjectStruct{s}.coords = getSubjectCoordinates(args.coords,map);

-        timelineParams = timeline;

+        disp('fetching volume definitions, please wait');

+        subjectStruct{s}.volumes = spm_vol(getImageFileList(subjectStruct{s}.dir,sessionlist,args.mask));

-        % common params

-        calculateParams  = struct;

-        calculateParams.PROJECT_BASE_PATH    = PROJECT_BASE_PATH;

-        calculateParams.PROJECT_RESULT_PATH  = PROJECT_RESULT_PATH;

+        rawData = calculateImageData(subjectStruct{s}.volumes,subjectStruct{s}.coords)

-        calculateParams.RANDOMIZE       = 0;

-        calculateParams.sessionList     = 1:3;

-        

-        calculateParams.eventList       = classStruct.eventMatrix; %[9,11,13; 10,12,14];

-        

-        subjectSelection = subjects;

-        calculateParams.subjectSelection = subjectSelection;

-        

-        decode = claculateMultiSubjectDecodePerformance(timelineParams,calculateParams,paramModel);

-

-        display('Finished calculations.');

-        display('Plotting...');

-

-        plotParams                   = struct;

-        

-%         plotParams.SVMCROSSVAL_CROSSVAL_METHOD_DEF = SVMCROSSVAL_CROSSVAL_METHOD_DEF;

-        plotParams.CROSSVAL_METHOD     = calculateParams.CROSSVAL_METHOD;

-        

-        plotParams.nClasses          = length(calculateParams.classList);

-

-        plotParams.decodePerformance = decode.decodePerformance;

-        plotParams.rawTimeCourse     = decode.rawTimeCourse;

-        plotParams.SubjectID         = subjectSelection;

-        plotParams.smoothed          = boolToYesNoString(calculateParams.smoothed);

-

-        assignin('base','plotParams',plotParams);

-%         plotDecodePerformance(params.psthStart,params.psthEnd,params.nClasses,decode.decodeTable,params.frameShiftStart,params.frameShiftEnd,decode.rawTimeCourse);

-        plotDecodePerformance(timelineParams,plotParams);

-            

-        display('all done.');

+        disp('done');

+    end

 end

-%% subject loop

-function decode = claculateMultiSubjectDecodePerformance(timelineParams,calculateParams,paramModel)

-

-decode = struct;

-decode.decodePerformance = [];

-decode.rawTimeCourse     = [];

-

-for subjectCell = calculateParams.subjectSelection

-    SubjectID = cell2mat(subjectCell);

-    namehelper = strcat('s',SubjectID); %Vars can not start with numbers.

-

-    display('loading SPM.mat ...');

-    spm = load(fullfile(calculateParams.PROJECT_BASE_PATH,SubjectID,calculateParams.PROJECT_RESULT_PATH));

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

-

-    % per subject params..

-    subjectParams = struct;

-    

-    subjectParams.des             = spm.SPM;

-

-

-    subjectParams.voxelList       = mapVoxelList(voxelList,SubjectID);

-

-    

-    subjectParams.SubjectID       = SubjectID;

-    subjectParams.namehelper      = namehelper;

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

-

-    display(sprintf('calculating cross-validation performance time-shift for Subject %s. Please Wait. ...',SubjectID));

-    display('switching off all warnings');

-    warning_state               = warning('off','all');

-    display('calculating ...');

-    decode.(namehelper)         = calculateDecodePerformance(timelineParams,calculateParams,subjectParams);

-

-    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);

-end

-end

+% 

+% %         decode = claculateMultiSubjectDecodePerformance(timelineParams,calculateParams,paramModel);

+% 

+%         display('Finished calculations.');

+%         display('Plotting...');

+% 

+%         plotParams                   = struct;

+%         

+% %         plotParams.SVMCROSSVAL_CROSSVAL_METHOD_DEF = SVMCROSSVAL_CROSSVAL_METHOD_DEF;

+%         plotParams.CROSSVAL_METHOD     = calculateParams.CROSSVAL_METHOD;

+%         

+%         plotParams.nClasses          = length(calculateParams.classList);

+% 

+%         plotParams.decodePerformance = decode.decodePerformance;

+%         plotParams.rawTimeCourse     = decode.rawTimeCourse;

+%         plotParams.SubjectID         = subjectSelection;

+%         plotParams.smoothed          = boolToYesNoString(calculateParams.smoothed);

+% 

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

+% %         plotDecodePerformance(params.psthStart,params.psthEnd,params.nClasses,decode.decodeTable,params.frameShiftStart,params.frameShiftEnd,decode.rawTimeCourse);

+%         plotDecodePerformance(timelineParams,plotParams);

+%             

+%         display('all done.');

+% 

@@ -1,14 +1,15 @@

 function runROIImageMaskMode(args)

 subjects = args.subjects;

-mask     = ['^' cell2mat(args.mask) '.*\.img$'];

 nSubjects = size(subjects);

-sessionlist = 1:3;

+sessionlist = args.sessionList;

 for s = 1:nSubjects

     subjectStruct{s}.dir = fullfile(args.basedir,cell2mat(subjects(s)));

+    d = load(fullfile(subjectStruct{s}.dir,'results','SPM.mat'));

+    subjectStruct{s}.des = d.SPM;

     subjectStruct{s}.name = cell2mat(subjects(s));

     subjectStruct{s}.roiFile = ui_selectRoiImage(...

         sprintf('Select ROI Files for %s',subjectStruct{s}.name),...

@@ -21,12 +22,22 @@ for s = 1:nSubjects

     % load image data

     disp('fetching volume definitions, please wait');

-    subjectStruct{s}.volumes = spm_vol(getImageFileList(subjectStruct{s}.dir,sessionlist,mask));

+    subjectStruct{s}.volumes = spm_vol(getImageFileList(subjectStruct{s}.dir,sessionlist,args.mask));

     disp('computing volume values, please wait');

-    subjectStruct{s}.rawData = calculateRoiImageData(subjectStruct{s}.volumes,subjectStruct{s}.roiFile);

+    

+    rawData = calculateRoiImageData(subjectStruct{s}.volumes,subjectStruct{s}.roiFile);

     % calculate psth

+    pstopts.des = subjectStruct{s}.des;

+    pstopts.eventList = args.eventList;

+    pstopts.sessionList = sessionlist;

+    

+    assignin('base','pstopts',pstopts);

+    assignin('base','rawData',rawData);

+    disp('computing psth');

+    subjectStruct{s}.psth    = calculatePST(args.timeline,pstopts,rawData);

+    disp('done');

 end

 assignin('base','subjectStruct',subjectStruct);

@@ -281,18 +281,18 @@ function model = createFirstStepPanel(model,parent,DEFAULT)

         pNorm = uipanel(parent,'Title','Normalization','Position',cell2mat(main_grid(2,3)));

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

-        createLabel(pNorm,[0 0.75 1 0.25],'PST Normalization');

-        norm1Model = {'DUMMY norm A','DUMMY norm B'};

+        createLabel(pNorm,[0 0.75 1 0.25],'psth norm4SVM');

+        norm1Model = {'none','mean','minmax'};

         model.selNormPST = uicontrol(pNorm,'Style','popupmenu',...

             'Units','normalized',...

             'Position',[0.0 0.5 1 0.25],...

             'String',norm1Model,...

             'UserData',norm1Model,...

-            'Value',1);

+            'Value',2);

          set(model.selNormPST,'BackgroundColor','w');   

-        createLabel(pNorm,[0 0.25 1 0.25],'Class-Grouping Normalization');

-        norm2Model = {'DUMMY norm X','DUMMY norm Y'};

+        createLabel(pNorm,[0 0.25 1 0.25],'Col Bias removal');

+        norm2Model = {'on','off'};

         model.selNormClass = uicontrol(pNorm,'Style','popupmenu',...

             'Units','normalized',...

             'Position',[0.0 0.0 1 0.25],...

@@ -313,7 +313,7 @@ function model = createFirstStepPanel(model,parent,DEFAULT)

         btnRunButton2 = uicontrol(pButtons,'String','run full Brain Searchlight',...

             'Units','normalized','Position',[0.33 0 0.33 1]);

         set(btnRunButton2,'Callback',{@cbRunPreprocessing,model,'FBS'}); % set here, because of model.  

-        set(btnRunButton2,'Enable','on');

+        set(btnRunButton2,'Enable','off');

         btnRunButton3 = uicontrol(pButtons,'String','run ROI-Image processing',...

             'Units','normalized','Position',[0.66 0 0.33 1]);