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1 function write_mat_results_ismir12(filein, subrun, fileout)
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2 % write_mat_resutls_ismir12(filein, subrun, fileout)
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3 %
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4 % write results from result file into ismir12 generic format.
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5 % if subrun is a vector, the results are averaged over the
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6 % runs specified
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7
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8
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9 [out, stats, features, individual] = test_generic_display_results(filein, 0);
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10
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11 % ---
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12 % we get the single individual values and
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13 % ---
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14 for i = 1:numel(subrun)
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15 individual = individual(subrun);
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16
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17 % number of inctrain cycles
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18 n_inctrain = numel(individual.diag.inctrain);
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19
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20 % ---
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21 % ok_train_unused
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22 % ---
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23 values_ok_train_unused{i} = reshape([individual.diag.inctrain.ok_notin_train], [],n_inctrain);
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24 values_ok_train_unused{i} = values_ok_train_unused(1:2:end,:).*100;
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25
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26 mean_ok_train_unused{i} = mean(values_ok_train_unused, 1);
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27 var_ok_train_unused{i} = var(values_ok_train_unused,[], 1);
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28
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29 % ---
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30 % ok_train
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31 % ---
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32 values_ok_train{i} = reshape([individual.diag.inctrain.ok_train], [],n_inctrain);
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33 values_ok_train{i} = values_ok_train(1:2:end,:).*100;
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34
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35 mean_ok_train{i} = mean(values_ok_train, 1);
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36 var_ok_train{i} = var(values_ok_train,[], 1);
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37
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38 % ---
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39 % ok_test
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40 % ---
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41 values_ok_test{i} = reshape([individual.diag.inctrain.ok_test], [],n_inctrain);
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42 values_ok_test{i} = values_ok_test(1:2:end,:).*100;
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43
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44 mean_ok_test{i} = mean(values_ok_test, 1);
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45 var_ok_test{i} = var(values_ok_test,[], 1);
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46 end
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47
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48
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49
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50 clear ('out', 'stats', 'features', 'individual');
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51 save(fileout)
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