From dc4ab1f4e64d738d6c0b70f0b690a2359685080f Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Wed, 12 Oct 2016 21:32:27 +0200 Subject: physchem regression, correlation_filter for fingerprints --- lib/substance.rb | 60 -------------------------------------------------------- 1 file changed, 60 deletions(-) (limited to 'lib/substance.rb') diff --git a/lib/substance.rb b/lib/substance.rb index d271327..31c465e 100644 --- a/lib/substance.rb +++ b/lib/substance.rb @@ -5,64 +5,4 @@ module OpenTox field :dataset_ids, type: Array, default: [] end - def neighbors dataset_id:,prediction_feature_id:,descriptors:,similarity:,relevant_features:nil - # TODO enable empty dataset_id -> use complete db - case descriptors[:method] - when "fingerprint" - fingerprint_neighbors dataset_id:dataset_id, prediction_feature_id:prediction_feature_id, descriptors:descriptors, similarity:similarity - when "properties" - properties_neighbors dataset_id:dataset_id, prediction_feature_id:prediction_feature_id, descriptors:descriptors, similarity:similarity, relevant_features: relevant_features - else - bad_request_error "Descriptor method '#{descriptors[:method]}' not implemented." - end - end - - def fingerprint_neighbors dataset_id:,prediction_feature_id:,descriptors:,similarity: - neighbors = [] - dataset = Dataset.find(dataset_id) - dataset.substances.each do |substance| - values = dataset.values(substance,prediction_feature_id) - if values - query_descriptors = self.send(descriptors[:method].to_sym, descriptors[:type]) - candidate_descriptors = substance.send(descriptors[:method].to_sym, descriptors[:type]) - sim = Algorithm.run similarity[:method], [query_descriptors, candidate_descriptors] - neighbors << {"_id" => substance.id, "measurements" => values, "descriptors" => candidate_descriptors, "similarity" => sim} if sim >= similarity[:min] - end - end - neighbors.sort{|a,b| b["similarity"] <=> a["similarity"]} - end - - def properties_neighbors dataset_id:,prediction_feature_id:,descriptors:,similarity:,relevant_features: - neighbors = [] - dataset = Dataset.find(dataset_id) - weights = relevant_features.collect{|k,v| v["r"]**2} - means = relevant_features.collect{|k,v| v["mean"]} - standard_deviations = relevant_features.collect{|k,v| v["sd"]} - query_descriptors = relevant_features.keys.collect{|i| properties[i].is_a?(Array) ? properties[i].median : nil } - dataset.substances.each do |substance| - values = dataset.values(substance,prediction_feature_id) - # exclude nanoparticles with different core - # TODO validate exclusion - next if substance.is_a? Nanoparticle and substance.core != self.core - if values - candidate_descriptors = relevant_features.keys.collect{|i| substance.properties[i].is_a?(Array) ? substance.properties[i].median : nil } - q = [] - c = [] - w = [] - (0..relevant_features.size-1).each do |i| - # add only complete pairs - if query_descriptors[i] and candidate_descriptors[i] - w << weights[i] - # scale values - q << (query_descriptors[i] - means[i])/standard_deviations[i] - c << (candidate_descriptors[i] - means[i])/standard_deviations[i] - end - end - sim = Algorithm.run similarity[:method], [q, c, w] - neighbors << {"_id" => substance.id, "measurements" => values, "descriptors" => candidate_descriptors, "similarity" => sim} if sim >= similarity[:min] - end - end - neighbors.sort{|a,b| b["similarity"] <=> a["similarity"]} - end - end -- cgit v1.2.3