runCompetitionSubject1

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Making data

0001 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0002 %%% Making data
0003 clear trials classes;
0004 
0005 %clear global store of features
0006 global previousFeatures
0007 clear previousFeatures
0008 
0009 %load eegdata;
0010 global testTrials % loaded from .mat file in next load. runCV looks for this global variable
0011 load competition2005/subject1trials;
0012 
0013 tic;
0014 
0015 matfilename = 'allCompetitionSubject1FilteredFisher'
0016 
0017 subject = 1;
0018 tasks = [1 2 3];
0019 trialsi = 1:size(trials,2);
0020 
0021 %trials = squeeze(eegdata(subject,tasks,trials));
0022 %% Remove EOG channel
0023 %[nr,nc] = size(trials);
0024 %for r = 1:nr
0025 %for c = 1:nc
0026 %trials{r,c} = trials{r,c}(1:6,:);
0027 %end
0028 %end
0029 
0030 classes = repmat((1:length(tasks))',1,length(trialsi));
0031 
0032 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0033 %%% Specify common paramters
0034 validationRepetitions = 5; 
0035 validationFraction = 0.2;
0036 nchannels = 32;
0037 lags = 0:4
0038 %%% max lag multiplied by 8 for raw and proj representations
0039 lagsraw = 0:(max(lags)*8);
0040 lagsproj = 0:6;
0041 %%%window parms only for SVD and MSF
0042 winSizes = round(512/4) %62; %[512]; %[62 125];
0043 winShift = round(winSizes(1)/2)
0044 %%%
0045 meanSubtracts = 1; %[0 1];
0046 
0047 nModes = [1 5 10];
0048 
0049 fisherDims = 1:4 %[1 2 4 10]
0050 
0051 %lags = 0:1
0052 %validationRepetitions = 2;
0053 %lagsraw = 0:1
0054 %lagsproj = 0:1
0055 %winSizes=[62];
0056 %meanSubtracts = [1];
0057 
0058 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0059 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0060 %%% SVD basis vector representation
0061 
0062 clear parameterSets;
0063 k = 0;
0064 for winSize = winSizes
0065   for nl = lags
0066     for nmodes = nModes %4:maxNModes %nchannels*(nl+1)
0067       firstModeDelta = max([1,round(nmodes/2)]);
0068       for firstMode = 1:firstModeDelta:(nchannels*(nl+1))-nmodes+1
0069     for meanSubt = meanSubtracts
0070       for fisherDim = fisherDims
0071         k = k + 1;
0072         parameterSets(k).nlags = nl;
0073         parameterSets(k).winSize = winSize;
0074         parameterSets(k).winShift = winShift;
0075         parameterSets(k).firstMode = firstMode;
0076         parameterSets(k).nModes = nmodes;
0077         parameterSets(k).meanSubtract = meanSubt;
0078         parameterSets(k).fisherDim = fisherDim;
0079       end
0080     end
0081       end
0082     end
0083   end
0084 end
0085 
0086 %%% Run all experiments
0087 CV.svd = runCV(trials,classes,parameterSets,...
0088     validationFraction,validationRepetitions,...
0089     @makeSVDModes,@LDA,@selectModes);
0090 
0091   save(matfilename,'CV');
0092 
0093 %%% Display results
0094 
0095 summarizeTestResults(CV.svd);
0096 
0097 %%% !!!
0098 
0099 return; 
0100 
0101 
0102 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0103 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0104 %%% SVD projections representation
0105 
0106 clear parameterSets;
0107 k = 0;
0108 for nl = lagsproj
0109   for nModes = 1:maxNModes %nchannels*(1+min(4,nl))
0110     for firstMode = 1:(nchannels*(nl+1))-nModes+1
0111       for meanSubt = meanSubtracts
0112     k = k + 1;
0113     parameterSets(k).nlags = nl;
0114     parameterSets(k).firstMode = firstMode;
0115     parameterSets(k).nModes = nModes;
0116     parameterSets(k).meanSubtract = meanSubt;
0117       end
0118     end
0119   end
0120 end
0121 
0122 %%% Run all experiments
0123 CV.svdproj = runCV(trials,classes,parameterSets,...
0124     validationFraction,validationRepetitions,...
0125     @makeSVDProj,@LDA,@selectSamplesRows);
0126 
0127   save(matfilename,'CV');
0128 
0129 %%% Display results
0130 
0131 summarizeTestResults(CV.svdproj);
0132 
0133 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0134 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0135 %%% Raw lagged representation
0136 
0137 clear parameterSets;
0138 k = 0;
0139 for nl = lagsraw
0140   k = k + 1;
0141   parameterSets(k).nlags = nl;
0142 end
0143 
0144 %%% Run all experiments
0145 CV.raw = runCV(trials,classes,parameterSets,...
0146     validationFraction,validationRepetitions,...
0147     @makeRawEEGFeatures,@LDA,@selectSamples);
0148 
0149   save(matfilename,'CV');
0150 
0151 %%% Display results
0152 summarizeTestResults(CV.raw);
0153 
0154   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0155   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0156   %%% MSF basis vector representation
0157 
0158   clear parameterSets;
0159   k = 0;
0160   for winSize = winSizes
0161     for nl = lags
0162       for nModes = 1:maxNModes %min([nchannels*(nl+1),maxNModes])
0163     for firstMode = 1:(nchannels*(nl+1))-nModes+1
0164       for meanSubt = meanSubtracts
0165         k = k + 1;
0166         parameterSets(k).nlags = nl;
0167         parameterSets(k).winSize = winSize;
0168         parameterSets(k).winShift = winShift;
0169         parameterSets(k).firstMode = firstMode;
0170         parameterSets(k).nModes = nModes;
0171         parameterSets(k).meanSubtract = meanSubt;
0172       end
0173     end
0174       end
0175     end
0176   end
0177 
0178   %%% Run all experiments
0179   CV.msf = runCV(trials,classes,parameterSets,...
0180       validationFraction,validationRepetitions,...
0181       @makeMSFModes,@LDA,@selectModes);
0182 
0183   save(matfilename,'CV');
0184 
0185   %%% Display results
0186 
0187   summarizeTestResults(CV.msf);
0188 
0189 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0190 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0191 %%% MSF projections representation
0192 
0193 clear parameterSets;
0194 k = 0;
0195 for nl = lagsproj
0196   for nModes = 1:maxNModes %nchannels*(1+min(4,nl))
0197     for firstMode = 1:(nchannels*(nl+1))-nModes+1
0198       for meanSubt = meanSubtracts
0199     k = k + 1;
0200     parameterSets(k).nlags = nl;
0201     parameterSets(k).firstMode = firstMode;
0202     parameterSets(k).nModes = nModes;
0203     parameterSets(k).meanSubtract = meanSubt;
0204       end
0205     end
0206   end
0207 end
0208 
0209 %%% Run all experiments
0210 CV.msfproj = runCV(trials,classes,parameterSets,...
0211     validationFraction,validationRepetitions,...
0212     @makeMSFProj,@LDA,@selectSamplesRows);
0213 
0214   save(matfilename,'CV');
0215 
0216 %%% Display results
0217 
0218 summarizeTestResults(CV.msfproj);
0219 
0220 toc