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1 function [r, valididx, clip_ids, P] = ranking_from_comparison_Stober_diffs(nDatasets, nRuns)
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2
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3 global globalvars;
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4 global comparison;
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5 global comparison_ids;
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6
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7 % ---
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8 % get the standard test set
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9 % NOTE: we will keep the r and valididx, and just use
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10 % the rest of the data for determining the issing edges etc
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11 % ---
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12 load('comp_SimGraphMulti_SimDataDump', 'G', 'r', 'valididx', 'clip_ids');
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13 nData = sum(valididx > 0);
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14
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15 % ---
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16 % initialise the new partition
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17 % ---
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18 P = cvpartition_alltrain(nData, nDatasets * nRuns);
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19
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20
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21 for i = 1:nDatasets
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22
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23 % ---
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24 % create new Stober graph
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25 % ---
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26 Gstob = ClipSimGraphStober();
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27 Gstob.random_all_constraints_graph;
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28 Gdiff = G - ClipSimGraphMulti(Gstob.to_DiGraph());
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29
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30 % ---
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31 % get missing entries in stober similarity
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32 % ---
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33 idx = find_graph_in_valid(r, comparison_ids(clip_ids),valididx, Gdiff);
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34 lostData = sum(idx);
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35 if lostData ~= Gdiff.num_edges
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36 error ('Inconsistent Data: edges in gdiff could not be found');
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37 end
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38
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39 % ---
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40 % save entries in DataPartition (remove from valid sets)
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41 % NOTE: this is manhual intervention into Class territory :(
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42 % ---
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43 for j = 1:nRuns
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44 jd = j + (i-1) * nRuns;
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45 P.mtraining{jd} = ones(P.N, 1) - idx(valididx)';
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46 P.mtest{jd} = ones(P.N, 1) - idx(valididx)';
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47 P.TrainSize(jd) = P.N - lostData;
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48 P.TestSize(jd) = P.N - lostData;
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49 end
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50 end
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51 end
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52
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53 % ---
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54 % This finds all graphs edges in the ranking
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55 % ---
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56 function idx = find_graph_in_valid(r, clip_ids, valididx, G)
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57
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58 idx = zeros(1,size(r,1));
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59 for i = find(valididx)
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60
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61 a = clip_ids(i);
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62 b = clip_ids(r{i,1});
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63 c = clip_ids(r{i,2});
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64 if G.edge(a,b,c) > 0
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65 idx(i) = 1;
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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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