private/classify.m (fd18aa8) - SVMCrossVal.git

classify.m

function classify(varargin)

switch nargin
    case 1
        paramModel = varargin{1};
        %PROJECT_BASE_PATH = 'D:\Analyze\Stimolos';
        PROJECT_BASE_PATH = 'D:\Analyze\Choice\24pilot';
        PROJECT_RESULT_PATH = 'results\SPM.mat';
    otherwise
        error('spmtoolbox:SVMCrossVal:arginError','Please Specify action and parameter model');
end
       
        % common params
        calculateParams  = struct;
        calculateParams.smoothed        = getChkValue(paramModel.chkSmoothed);

calculateParams.frameShiftStart = getDouble(paramModel.txtFrameShiftStart);  % -20;
        calculateParams.frameShiftEnd   = getDouble(paramModel.txtFrameShiftEnd); %15;
        calculateParams.decodeDuration  = getDouble(paramModel.txtFrameShiftDur);
        calculateParams.psthStart       = getDouble(paramModel.txtPSTHStart); % -25;
        calculateParams.psthEnd         = getDouble(paramModel.txtPSTHEnd); % 20;
        calculateParams.baselineStart   = getDouble(paramModel.txtBaselineStart); % -22;
        calculateParams.baselineEnd     = getDouble(paramModel.txtBaselineEnd); % -20;

calculateParams.svmargs         = get(paramModel.txtSVMopts,'String');
        calculateParams.sessionList     = 1:3;

classStruct = parseClassDef(paramModel);
        
        
        calculateParams.labelMap        = LabelMap(classStruct.labelCells , classStruct.conditionCells, 'auto'); % LabelMap({'<','>','<+<','>+>','<+>','>+<'},{-2,-1,1,2,3,4}); 0 is autolabel
        calculateParams.classList       = getClasses(calculateParams.labelMap);
        calculateParams.eventList       = classStruct.eventMatrix; %[9,11,13; 10,12,14];
%         calculateParams.eventList       = getPSTEventMatrix(calculateParams.labelMap);
        
        subjectSelection = getSubjectIDString(paramModel);
        decode = struct;
        decode.decodePerformance = [];
        decode.rawTimeCourse     = [];
        
        for subjectCell = subjectSelection
            SubjectID = cell2mat(subjectCell);
            namehelper = strcat('s',SubjectID); %Vars can not start with numbers.

display('loading SPM.mat ...');
            spm = load(fullfile(PROJECT_BASE_PATH,SubjectID,PROJECT_RESULT_PATH));
            display('... done.');

%% calculate
            calculateParams.(namehelper).des             = spm.SPM;
            calculateParams.(namehelper).voxelList       = parseVoxelList(paramModel,SubjectID);
            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(calculateParams,SubjectID);
            
            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

display('Finished calculations.');
        display('Plotting...');

plotParams                   = struct;
        plotParams.psthStart         = calculateParams.psthStart;
        plotParams.psthEnd           = calculateParams.psthEnd;
        plotParams.nClasses          = length(calculateParams.classList);
        
        plotParams.frameShiftStart   = calculateParams.frameShiftStart;
        plotParams.frameShiftEnd     = calculateParams.frameShiftEnd;
        plotParams.decodePerformance = decode.decodePerformance;
        plotParams.rawTimeCourse     = decode.rawTimeCourse;
        
        if numel(subjectSelection) == 1
          plotParams.SubjectID         = SubjectID;
        else
          plotParams.SubjectID         = 'Multiple';
        end

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(plotParams);
            
        display('all done.');
    end

SVMCrossVal.git

added 2nd classification method: no crossval, but class performance checks. may not plot correctly with multisubject