physchem regression, correlation_filter for fingerprints

1 files changed, 0 insertions, 60 deletions

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