2nd v

1 files changed, 46 insertions, 41 deletions

diff --git a/lib/model.rb b/lib/model.rb
index bebf5d3..f4df8ea 100644
--- a/lib/model.rb
+++ b/lib/model.rb
@@ -177,7 +177,7 @@ module OpenTox
         return @prediction_dataset if database_activity(subjectid)
 
 
-       if metadata[RDF.type] == [OTA.ClassificationLazySingleTarget]
+        if metadata[RDF.type] == [OTA.ClassificationLazySingleTarget]
           # AM: Balancing, see http://www.maunz.de/wordpress/opentox/2011/balanced-lazar
           l = Array.new # larger 
           s = Array.new # smaller fraction
@@ -211,33 +211,33 @@ module OpenTox
           neighbors_best=nil
 
           begin
-          for i in 1..modulo[0] do
-            (i == modulo[0]) && (slack>0) ? lr_size = s.size + slack : lr_size = s.size + addon  # determine fraction
-            LOGGER.info "BLAZAR: Neighbors round #{i}: #{position} + #{lr_size}."
-            neighbors_balanced(s, l, position, lr_size) # get ratio fraction of larger part
-            prop_matrix = get_prop_matrix
-            prediction = eval("#{@prediction_algorithm}(@neighbors,{:similarity_algorithm => @similarity_algorithm, :p_values => @p_values})")
-            if prediction_best.nil? || prediction[:confidence].abs > prediction_best[:confidence].abs 
-              prediction_best=prediction 
-              neighbors_best=@neighbors
+            for i in 1..modulo[0] do
+              (i == modulo[0]) && (slack>0) ? lr_size = s.size + slack : lr_size = s.size + addon  # determine fraction
+              LOGGER.info "BLAZAR: Neighbors round #{i}: #{position} + #{lr_size}."
+              neighbors_balanced(s, l, position, lr_size) # get ratio fraction of larger part
+              props = get_props
+              prediction = eval("#{@prediction_algorithm}(@neighbors,{:similarity_algorithm => @similarity_algorithm, :p_values => @p_values})")
+              if prediction_best.nil? || prediction[:confidence].abs > prediction_best[:confidence].abs 
+                prediction_best=prediction 
+                neighbors_best=@neighbors
+              end
+              position = position + lr_size
             end
-            position = position + lr_size
-          end
           rescue Exception => e
             LOGGER.error "BLAZAR failed in prediction: "+e.class.to_s+": "+e.message
           end
 
           prediction=prediction_best
           @neighbors=neighbors_best
-         ### END AM balanced predictions
+          ### END AM balanced predictions
 
         else # regression case: no balancing
           neighbors
-          prop_matrix = get_prop_matrix
+          props = get_props
           prediction = eval("#{@prediction_algorithm}(@neighbors,{:similarity_algorithm => @similarity_algorithm, :p_values => @p_values})")
         end
-        
-       # TODO: reasonable feature name
+
+        # TODO: reasonable feature name
         #prediction_feature_uri = File.join( @prediction_dataset.uri, "feature", "prediction", File.basename(@metadata[OT.dependentVariables]),@prediction_dataset.compounds.size.to_s)
         value_feature_uri = File.join( @prediction_dataset.uri, "feature", "prediction", File.basename(@metadata[OT.dependentVariables]),"value")
         confidence_feature_uri = File.join( @prediction_dataset.uri, "feature", "prediction", File.basename(@metadata[OT.dependentVariables]),"confidence")
@@ -245,7 +245,7 @@ module OpenTox
         prediction_feature_uris = {value_feature_uri => prediction[:prediction], confidence_feature_uri => prediction[:confidence]}
         #prediction_feature_uris[value_feature_uri] = "No similar compounds in training dataset." if @neighbors.size == 0 or prediction[:prediction].nil?
         prediction_feature_uris[value_feature_uri] = nil if @neighbors.size == 0 or prediction[:prediction].nil?
-        
+
         #@prediction_dataset.metadata[OT.dependentVariables] = prediction_feature_uri
         @prediction_dataset.metadata[OT.dependentVariables] = @metadata[OT.dependentVariables]
 
@@ -275,10 +275,10 @@ module OpenTox
             DC.title => URI.decode(File.basename( @metadata[OT.dependentVariables] )),
             # TODO: factor information to value
           })
-            #OT.prediction => prediction[:prediction],
-            #OT.confidence => prediction[:confidence],
-            #OT.parameters => [{DC.title => "compound_uri", OT.paramValue => compound_uri}]
-            @prediction_dataset.add @compound.uri, prediction_feature_uri, value
+          #OT.prediction => prediction[:prediction],
+          #OT.confidence => prediction[:confidence],
+          #OT.parameters => [{DC.title => "compound_uri", OT.paramValue => compound_uri}]
+          @prediction_dataset.add @compound.uri, prediction_feature_uri, value
         end
 
         if verbose
@@ -341,34 +341,39 @@ module OpenTox
       end
 
       # Calculate the propositionalization matrix aka instantiation matrix (0/1 entries for features)
-      def get_prop_matrix
+      # Same for the vector describing the query compound
+      def get_props
         matrix = Array.new
         begin 
-        @neighbors.each do |n|
-          n = n[:compound]
+          @neighbors.each do |n|
+            n = n[:compound]
+            row = []
+            @features.each do |f|
+              if ! @fingerprints[n].nil? 
+                row << (@fingerprints[n].include?(f) ? 0.0 : @p_values[f])
+              else
+                row << 0.0
+              end
+            end
+            matrix << row
+          end
           row = []
           @features.each do |f|
-            if ! @fingerprints[n].nil? 
-              row << (@fingerprints[n].include?(f) ? 0.0 : @p_values[f])
-            else
-              row << 0.0
-            end
+            row << (@compound.match([f]).size == 0 ? 0.0 : @p_values[f])
           end
-          matrix << row
-        end
         rescue Exception => e
-          LOGGER.debug "get_prop_matrix failed with '" + $! + "'"
+          LOGGER.debug "get_props failed with '" + $! + "'"
         end
-        matrix
+        [ matrix, row ]
       end
 
       # Find neighbors and store them as object variable, access only a subset of compounds for that.
       def neighbors_balanced(s, l, start, offset)
         @compound_features = eval("#{@feature_calculation_algorithm}(@compound,@features)") if @feature_calculation_algorithm
         @neighbors = []
-          [ l[start, offset ] , s ].flatten.each do |training_compound| # AM: access only a balanced subset
-            training_features = @fingerprints[training_compound]
-            add_neighbor training_features, training_compound
+        [ l[start, offset ] , s ].flatten.each do |training_compound| # AM: access only a balanced subset
+          training_features = @fingerprints[training_compound]
+          add_neighbor training_features, training_compound
         end
 
       end
@@ -378,7 +383,7 @@ module OpenTox
         @compound_features = eval("#{@feature_calculation_algorithm}(@compound,@features)") if @feature_calculation_algorithm
         @neighbors = []
         @fingerprints.each do |training_compound,training_features| # AM: access all compounds
-           add_neighbor training_features, training_compound
+          add_neighbor training_features, training_compound
         end
       end
 
@@ -388,10 +393,10 @@ module OpenTox
         if sim > @min_sim
           @activities[training_compound].each do |act|
             @neighbors << {
-               :compound => training_compound,
-               :similarity => sim,
-               :features => training_features,
-               :activity => act
+              :compound => training_compound,
+              :similarity => sim,
+              :features => training_features,
+              :activity => act
             }
           end
         end