SVMCrossVal.git

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function plotDecodePerformance(type,decode,subjectData)
header = decode.header;
timeline = header.timeline;
frameshift = header.frameShift;
psthStart         = timeline.psthStart;
psthEnd           = timeline.psthEnd;
frameStart        = frameshift.frameShiftStart;
frameEnd          = frameshift.frameShiftEnd;
nClasses          = numel(header.classDef.labelCells);
decodePerformance = decode.decodePerformance;
psth              = decode.rawTimeCourse;
SubjectID         = subjectData;
nSubjects         = size(SubjectID,2);
    f = figure;
    subplot(2,1,1); 
        plotPSTH(psth,psthStart,psthEnd);
    
    % plot performance timeline
    subplot(2,1,2)    
    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 [%]');
    switch type
        case 'simple'
            plotDecodePerformanceWithSE(frameStart,frameEnd,decodePerformance)
        case 'class performance'
            plotClassPerformance(frameStart,frameEnd,decodePerformance,nClasses)
        case 'x-subject-val'
            for c = 1:nSubjects
                plot(frameStart:frameEnd, decodePerformance(:,c) ,[colorChooser(mod(c,nSubjects)+3) '-']);
            end
            plotDecodePerformanceWithSE(frameStart,frameEnd,decodePerformance)
    end
    hold off;
    
%     setTitle(f,header,decode,subjectData);
    
end
 
 
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