SVMCrossVal.git

plotDecodePerformance.m   1) function plotDecodePerformance(timeline,inputStruct)

plotDecodePerformance.m   2) 
plotDecodePerformance.m   3) global CROSSVAL_METHOD_DEF;

plotDecodePerformance.m   4) 

plotDecodePerformance.m   5) PSTH_AXIS_MIN = -1;
plotDecodePerformance.m   6) PSTH_AXIS_MAX = 1;

plotDecodePerformance.m   7) 

plotDecodePerformance.m   8)         psthStart         = timeline.psthStart;
plotDecodePerformance.m   9)         psthEnd           = timeline.psthEnd;
plotDecodePerformance.m  10)         frameStart        = timeline.frameShiftStart;
plotDecodePerformance.m  11)         frameEnd          = timeline.frameShiftEnd;

plotDecodePerformance.m  12) 
plotDecodePerformance.m  13)         nClasses          = inputStruct.nClasses;
plotDecodePerformance.m  14)         decodePerformance = inputStruct.decodePerformance;
plotDecodePerformance.m  15)         psth              = inputStruct.rawTimeCourse;
plotDecodePerformance.m  16)         SubjectID         = inputStruct.SubjectID;
plotDecodePerformance.m  17)         smoothed          = inputStruct.smoothed;

plotDecodePerformance.m  18)         PLOT_METHOD       = inputStruct.CROSSVAL_METHOD;

plotDecodePerformance.m  19) %         CROSSVAL_METHOD_DEF = inputStruct.CROSSVAL_METHOD_DEF;

plotDecodePerformance.m  20) 

plotDecodePerformance.m  21) 
plotDecodePerformance.m  22)     f = figure;
plotDecodePerformance.m  23)     subplot(2,1,1);
plotDecodePerformance.m  24)     hold on;
plotDecodePerformance.m  25)       for voxel = 1:size(psth,2)
plotDecodePerformance.m  26)           for label = 1:size(psth{voxel},2)
plotDecodePerformance.m  27)               psthData = [];
plotDecodePerformance.m  28)               for timepoint = 1:size(psth{voxel}{label},2)

plotDecodePerformance.m  29)                   psthData = nanmean(psth{voxel}{label});

plotDecodePerformance.m  30)               end
plotDecodePerformance.m  31)               plot(psthStart:psthEnd,psthData,[colorChooser(voxel), lineStyleChooser(label)]);
plotDecodePerformance.m  32)           end
plotDecodePerformance.m  33)       end

plotDecodePerformance.m  34)     axis([psthStart psthEnd PSTH_AXIS_MIN PSTH_AXIS_MAX])

plotDecodePerformance.m  35)     xlabel('time [sec]');
plotDecodePerformance.m  36)     ylabel('fMRI-signal change [%]');

plotDecodePerformance.m  37)     hold off
plotDecodePerformance.m  38)     
plotDecodePerformance.m  39)     subplot(2,1,2)    
plotDecodePerformance.m  40)     hold on;

plotDecodePerformance.m  41)     

plotDecodePerformance.m  42)     chanceLevel = 100/nClasses;
plotDecodePerformance.m  43)     goodPredictionLevel = chanceLevel*1.5;

plotDecodePerformance.m  44)     plot([psthStart psthEnd],[chanceLevel chanceLevel],'k:');
plotDecodePerformance.m  45)     plot([psthStart psthEnd],[goodPredictionLevel goodPredictionLevel],'k:');

plotDecodePerformance.m  46)     axis([psthStart psthEnd 0 100])

plotDecodePerformance.m  47)     xlabel('time [sec]');
plotDecodePerformance.m  48)     ylabel('decode performance [%]');
plotDecodePerformance.m  49)     

plotDecodePerformance.m  50)     

plotDecodePerformance.m  51)     

plotDecodePerformance.m  52)     switch PLOT_METHOD

plotDecodePerformance.m  53)         case CROSSVAL_METHOD_DEF.svmcrossval
plotDecodePerformance.m  54)             plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b','LineWidth',2);

plotDecodePerformance.m  55) 
plotDecodePerformance.m  56)             se = myStdErr(decodePerformance,2);
plotDecodePerformance.m  57)             plot(frameStart:frameEnd, mean(decodePerformance,2)+se ,'b:');
plotDecodePerformance.m  58)             plot(frameStart:frameEnd, mean(decodePerformance,2)-se ,'b:');

plotDecodePerformance.m  59)         case CROSSVAL_METHOD_DEF.classPerformance

plotDecodePerformance.m  60)             for c = 1:size(decodePerformance,2)
plotDecodePerformance.m  61)                 plot(frameStart:frameEnd, decodePerformance(:,c) ,[colorChooser(mod(c,nClasses)+3) '-']);
plotDecodePerformance.m  62)             end
plotDecodePerformance.m  63) 
plotDecodePerformance.m  64)             plot(frameStart:frameEnd, mean(decodePerformance,2) ,'b','LineWidth',2);
plotDecodePerformance.m  65) 
plotDecodePerformance.m  66)     end

plotDecodePerformance.m  67)     
plotDecodePerformance.m  68)     

plotDecodePerformance.m  69)     hold off;

plotDecodePerformance.m  70)     

plotDecodePerformance.m  71)     nSubjects = size(SubjectID,2);
plotDecodePerformance.m  72)     nVoxelPerSubject = size(psth,2)/size(SubjectID,2);
plotDecodePerformance.m  73)     
plotDecodePerformance.m  74)     if strcmp(smoothed,'yes')
plotDecodePerformance.m  75)         smoothedString = 'using smoothed data';
plotDecodePerformance.m  76)     else
plotDecodePerformance.m  77)         smoothedString = 'using unsmoothed data';
plotDecodePerformance.m  78)     end
plotDecodePerformance.m  79)     
plotDecodePerformance.m  80)     if nSubjects == 1
plotDecodePerformance.m  81)         subjectName = cell2Mat(SubjectID);
plotDecodePerformance.m  82)         title = sprintf('Subject %s, over %g voxel, %s',subjectName,nVoxelPerSubject,smoothedString);
plotDecodePerformance.m  83)     else
plotDecodePerformance.m  84)         title = sprintf('%g Subjects, %g Voxel per Subject, %s',nSubjects,nVoxelPerSubject,smoothedString);
plotDecodePerformance.m  85)     end
plotDecodePerformance.m  86)     

plotDecodePerformance.m  87) 
plotDecodePerformance.m  88)     set(f,'Name',title);
plotDecodePerformance.m  89)     display(sprintf('%s',title));
plotDecodePerformance.m  90) 
plotDecodePerformance.m  91) 
plotDecodePerformance.m  92) 
plotDecodePerformance.m  93) end
plotDecodePerformance.m  94) 

plotDecodePerformance.m  95) 

plotDecodePerformance.m  96) function color = colorChooser(n)
plotDecodePerformance.m  97)     switch (mod(n,8))
plotDecodePerformance.m  98)     case 0
plotDecodePerformance.m  99)         color = 'r';

plotDecodePerformance.m 100)     case 1
plotDecodePerformance.m 101)         color = 'g';

plotDecodePerformance.m 102)     case 2
plotDecodePerformance.m 103)         color = 'b';
plotDecodePerformance.m 104)     case 3

plotDecodePerformance.m 105)         color = 'c';
plotDecodePerformance.m 106)     case 4
plotDecodePerformance.m 107)         color = 'm';
plotDecodePerformance.m 108)     case 5
plotDecodePerformance.m 109)         color = 'y';

plotDecodePerformance.m 110)     otherwise
plotDecodePerformance.m 111)         color = 'k';
plotDecodePerformance.m 112)     end
plotDecodePerformance.m 113) end
plotDecodePerformance.m 114) 
plotDecodePerformance.m 115) function style = lineStyleChooser(n)
plotDecodePerformance.m 116) switch(mod(n,4))
plotDecodePerformance.m 117)     case 0
plotDecodePerformance.m 118)       style = '--';
plotDecodePerformance.m 119)     case 1
plotDecodePerformance.m 120)         style = '-';
plotDecodePerformance.m 121)     case 2 
plotDecodePerformance.m 122)         style = ':';
plotDecodePerformance.m 123)     case 3

plotDecodePerformance.m 124)         style = '-.';