wolffd@0: function  sim_from_comparison_attach_weights(filen)
wolffd@0: 
wolffd@0: global comparison;
wolffd@0: global comparison_ids;
wolffd@0: % load data from mat file
wolffd@0: load(filen);
wolffd@0: 
wolffd@0: % ---
wolffd@0: % get the similarity multigraph and remove cycles
wolffd@0: % ---
wolffd@0: cprint(2, 'creating graph')
wolffd@0: Gm = ClipSimGraphMulti(comparison, comparison_ids);
wolffd@0: Gm.remove_cycles_length2; 
wolffd@0: 
wolffd@0: nTestSets = size(partBinTst, 2); % num cv bins
wolffd@0: ntrainsizes = size(partBinTrn, 2); % num increases of training
wolffd@0: 
wolffd@0: % ---
wolffd@0: % test sets
wolffd@0: % ---
wolffd@0: cprint(2, 'doing test sets')
wolffd@0: 
wolffd@0: % for all validations 
wolffd@0: for k = 1:size(partBinTst, 2);
wolffd@0:     
wolffd@0:     % for each constraint tiplet
wolffd@0:     for i = 1:size(partBinTst{k},1)
wolffd@0:         
wolffd@0:         % get weight for this edge from graph
wolffd@0:         [weight, ~, ~] = Gm.edge(partBinTst{k}(i,1), partBinTst{k}(i,2),...
wolffd@0:             partBinTst{k}(i,3));
wolffd@0:             
wolffd@0:             if isempty(weight) || weight == 0
wolffd@0:                 error 'inconsistent similarity data';
wolffd@0:             end
wolffd@0:         
wolffd@0:         % save into same data structure
wolffd@0:         partBinTst{k}(i,4) = weight;
wolffd@0:     end
wolffd@0: end
wolffd@0: 
wolffd@0: % ---
wolffd@0: % train sets
wolffd@0: % ---
wolffd@0: 
wolffd@0: cprint(2, 'doing train sets')
wolffd@0: % for all validations 
wolffd@0: for k = 1:size(partBinTrn, 1);
wolffd@0:     
wolffd@0:     % for all training sizes
wolffd@0:     for m = 1:size(partBinTrn, 2);
wolffd@0:         
wolffd@0:         % for each constraint tiplet
wolffd@0:         for i = 1:size(partBinTrn{k,m},1)
wolffd@0: 
wolffd@0:             % get weight for this edge from graph
wolffd@0:             [weight, ~, ~] = Gm.edge(partBinTrn{k,m}(i,1), partBinTrn{k,m}(i,2),...
wolffd@0:                 partBinTrn{k,m}(i,3));
wolffd@0:             
wolffd@0:             if isempty(weight) || weight == 0
wolffd@0:                 error 'inconsistent similarity data';
wolffd@0:             end
wolffd@0:             
wolffd@0:             % save into same data structure
wolffd@0:             partBinTrn{k,m}(i,4) = weight;
wolffd@0:         end
wolffd@0:     end
wolffd@0: end
wolffd@0: 
wolffd@0: % ---
wolffd@0: % Notrain sets
wolffd@0: % ---
wolffd@0: cprint(2, 'doing Notrain sets')
wolffd@0: % for all validations 
wolffd@0: for k = 1:size(partBinNoTrn, 1);
wolffd@0:     
wolffd@0:     % for all training sizes
wolffd@0:     for m = 1:size(partBinNoTrn, 2);
wolffd@0:         
wolffd@0:         % for each constraint tiplet
wolffd@0:         for i = 1:size(partBinNoTrn{k,m},1)
wolffd@0: 
wolffd@0:             % get weight for this edge from graph
wolffd@0:             [weight, ~, ~] = Gm.edge(partBinNoTrn{k,m}(i,1), partBinNoTrn{k,m}(i,2),...
wolffd@0:                 partBinNoTrn{k,m}(i,3));
wolffd@0:             
wolffd@0:             if isempty(weight) || weight == 0
wolffd@0:                 error 'inconsistent similarity data';
wolffd@0:             end
wolffd@0:             % save into same data structure
wolffd@0:             partBinNoTrn{k,m}(i,4) = weight;
wolffd@0:         end
wolffd@0:     end
wolffd@0: end
wolffd@0: 
wolffd@0: % save results to mat file
wolffd@0: save(sprintf('%s_weighted.mat',filen), 'partBinTst', 'partBinTrn', 'partBinNoTrn');