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1 function sim_from_comparison_attach_weights(filen)
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2
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3 global comparison;
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4 global comparison_ids;
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5 % load data from mat file
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6 load(filen);
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7
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8 % ---
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9 % get the similarity multigraph and remove cycles
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10 % ---
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11 cprint(2, 'creating graph')
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12 Gm = ClipSimGraphMulti(comparison, comparison_ids);
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13 Gm.remove_cycles_length2;
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14
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15 nTestSets = size(partBinTst, 2); % num cv bins
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16 ntrainsizes = size(partBinTrn, 2); % num increases of training
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17
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18 % ---
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19 % test sets
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20 % ---
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21 cprint(2, 'doing test sets')
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22
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23 % for all validations
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24 for k = 1:size(partBinTst, 2);
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25
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26 % for each constraint tiplet
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27 for i = 1:size(partBinTst{k},1)
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28
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29 % get weight for this edge from graph
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30 [weight, ~, ~] = Gm.edge(partBinTst{k}(i,1), partBinTst{k}(i,2),...
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31 partBinTst{k}(i,3));
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32
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33 if isempty(weight) || weight == 0
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34 error 'inconsistent similarity data';
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35 end
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36
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37 % save into same data structure
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38 partBinTst{k}(i,4) = weight;
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39 end
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40 end
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41
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42 % ---
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43 % train sets
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44 % ---
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45
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46 cprint(2, 'doing train sets')
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47 % for all validations
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48 for k = 1:size(partBinTrn, 1);
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49
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50 % for all training sizes
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51 for m = 1:size(partBinTrn, 2);
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52
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53 % for each constraint tiplet
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54 for i = 1:size(partBinTrn{k,m},1)
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55
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56 % get weight for this edge from graph
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57 [weight, ~, ~] = Gm.edge(partBinTrn{k,m}(i,1), partBinTrn{k,m}(i,2),...
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58 partBinTrn{k,m}(i,3));
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59
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60 if isempty(weight) || weight == 0
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61 error 'inconsistent similarity data';
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62 end
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63
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64 % save into same data structure
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65 partBinTrn{k,m}(i,4) = weight;
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66 end
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67 end
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68 end
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69
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70 % ---
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71 % Notrain sets
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72 % ---
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73 cprint(2, 'doing Notrain sets')
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74 % for all validations
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75 for k = 1:size(partBinNoTrn, 1);
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76
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77 % for all training sizes
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78 for m = 1:size(partBinNoTrn, 2);
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79
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80 % for each constraint tiplet
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81 for i = 1:size(partBinNoTrn{k,m},1)
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82
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83 % get weight for this edge from graph
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84 [weight, ~, ~] = Gm.edge(partBinNoTrn{k,m}(i,1), partBinNoTrn{k,m}(i,2),...
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85 partBinNoTrn{k,m}(i,3));
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86
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87 if isempty(weight) || weight == 0
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88 error 'inconsistent similarity data';
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89 end
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90 % save into same data structure
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91 partBinNoTrn{k,m}(i,4) = weight;
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92 end
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93 end
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94 end
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95
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96 % save results to mat file
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97 save(sprintf('%s_weighted.mat',filen), 'partBinTst', 'partBinTrn', 'partBinNoTrn');
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