runAll2

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

0001 
0002 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0003 %%% Making data
0004 clear trials classes;
0005 
0006 load eegdata;
0007 
0008 matfilename = 'allCVsubject2'
0009 
0010 subject = 2;
0011 tasks = [1 2 3 4 5];
0012 trials = 1:5;
0013 
0014 trials = squeeze(eegdata(subject,tasks,trials));
0015 % Remove EOG channel
0016 [nr,nc] = size(trials);
0017 for r = 1:nr
0018   for c = 1:nc
0019     trials{r,c} = trials{r,c}(1:6,:);
0020   end
0021 end
0022 
0023 classes = repmat((1:length(tasks))',1,length(trials));
0024 
0025 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0026 %%% Specify common paramters
0027 validationRepetitions = 5;
0028 validationFraction = 0.2;
0029 nchannels = 6;
0030 lags = 0:4;
0031 %%% max lag multiplied by 8 for raw and proj representations
0032 lagsraw = 0:(max(lags)*8);
0033 lagsproj = 0:6;
0034 %%%window parms only for SVD and MSF
0035 winSizes = [62 125];
0036 winShift = 32;
0037 %%%
0038 meanSubtracts = [0 1];
0039 
0040 
0041 if 1
0042   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0043   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0044   %%% MSF basis vector representation
0045 
0046   clear parameterSets;
0047   k = 0;
0048   for winSize = winSizes
0049     for nl = lags
0050       for nModes = 1:nchannels*(nl+1)
0051     for firstMode = 1:(nchannels*(nl+1))-nModes+1
0052       for meanSubt = meanSubtracts
0053         k = k + 1;
0054         parameterSets(k).nlags = nl;
0055         parameterSets(k).winSize = winSize;
0056         parameterSets(k).winShift = winShift;
0057         parameterSets(k).firstMode = firstMode;
0058         parameterSets(k).nModes = nModes;
0059         parameterSets(k).meanSubtract = meanSubt;
0060       end
0061     end
0062       end
0063     end
0064   end
0065 
0066   %%% Run all experiments
0067   CV.msf = runCV(trials,classes,parameterSets,...
0068       validationFraction,validationRepetitions,...
0069       @makeMSFModes,@LDA,@selectModes);
0070 
0071   save(matfilename,'CV');
0072 
0073   %%% Display results
0074 
0075   summarizeTestResults(CV.msf);
0076 
0077 end
0078 
0079 if 1
0080   
0081 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0082 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0083 %%% MSF projections representation
0084 
0085 clear parameterSets;
0086 k = 0;
0087 for nl = lagsproj
0088   for nModes = 1:nchannels*(1+min(4,nl))
0089     for firstMode = 1:(nchannels*(nl+1))-nModes+1
0090       for meanSubt = meanSubtracts
0091     k = k + 1;
0092     parameterSets(k).nlags = nl;
0093     parameterSets(k).firstMode = firstMode;
0094     parameterSets(k).nModes = nModes;
0095     parameterSets(k).meanSubtract = meanSubt;
0096       end
0097     end
0098   end
0099 end
0100 
0101 %%% Run all experiments
0102 CV.msfproj = runCV(trials,classes,parameterSets,...
0103     validationFraction,validationRepetitions,...
0104     @makeMSFProj,@LDA,@selectSamplesRows);
0105 
0106   save(matfilename,'CV');
0107 
0108 %%% Display results
0109 
0110 summarizeTestResults(CV.msfproj);
0111 
0112 end
0113 
0114 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0115 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0116 %%% SVD basis vector representation
0117 
0118 clear parameterSets;
0119 k = 0;
0120 for winSize = winSizes
0121   for nl = lags
0122     for nModes = 1:nchannels*(nl+1)
0123       for firstMode = 1:(nchannels*(nl+1))-nModes+1
0124     for meanSubt = meanSubtracts
0125       k = k + 1;
0126       parameterSets(k).nlags = nl;
0127       parameterSets(k).winSize = winSize;
0128       parameterSets(k).winShift = winShift;
0129       parameterSets(k).firstMode = firstMode;
0130       parameterSets(k).nModes = nModes;
0131       parameterSets(k).meanSubtract = meanSubt;
0132     end
0133       end
0134     end
0135   end
0136 end
0137 
0138 %%% Run all experiments
0139 CV.svd = runCV(trials,classes,parameterSets,...
0140     validationFraction,validationRepetitions,...
0141     @makeSVDModes,@LDA,@selectModes);
0142 
0143   save(matfilename,'CV');
0144 
0145 %%% Display results
0146 
0147 summarizeTestResults(CV.svd);
0148 
0149 
0150 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0151 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0152 %%% SVD projections representation
0153 
0154 clear parameterSets;
0155 k = 0;
0156 for nl = lagsproj
0157   for nModes = 1:nchannels*(1+min(4,nl))
0158     for firstMode = 1:(nchannels*(nl+1))-nModes+1
0159       for meanSubt = meanSubtracts
0160     k = k + 1;
0161     parameterSets(k).nlags = nl;
0162     parameterSets(k).firstMode = firstMode;
0163     parameterSets(k).nModes = nModes;
0164     parameterSets(k).meanSubtract = meanSubt;
0165       end
0166     end
0167   end
0168 end
0169 
0170 %%% Run all experiments
0171 CV.svdproj = runCV(trials,classes,parameterSets,...
0172     validationFraction,validationRepetitions,...
0173     @makeSVDProj,@LDA,@selectSamplesRows);
0174 
0175   save(matfilename,'CV');
0176 
0177 %%% Display results
0178 
0179 summarizeTestResults(CV.svdproj);
0180 
0181 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0182 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0183 %%% Raw lagged representation
0184 
0185 clear parameterSets;
0186 k = 0;
0187 for nl = lagsraw
0188   k = k + 1;
0189   parameterSets(k).nlags = nl;
0190 end
0191 
0192 %%% Run all experiments
0193 CV.raw = runCV(trials,classes,parameterSets,...
0194     validationFraction,validationRepetitions,...
0195     @makeRawEEGFeatures,@LDA,@selectSamples);
0196 
0197   save(matfilename,'CV');
0198 
0199 %%% Display results
0200 summarizeTestResults(CV.raw);
0201