dataset folds fixed

4 files changed, 20 insertions, 43 deletions

diff --git a/lib/crossvalidation.rb b/lib/crossvalidation.rb
index 2e44ff2..4f61ff4 100644
--- a/lib/crossvalidation.rb
+++ b/lib/crossvalidation.rb
@@ -29,16 +29,14 @@ module OpenTox
         training_dataset = model.training_dataset
         training_dataset.folds(n).each_with_index do |fold,fold_nr|
           #fork do # parallel execution of validations can lead to Rserve and memory problems
-            $logger.debug "Dataset #{training_dataset.name}: Fold #{fold_nr} started"
-            t = Time.now
-            validation = TrainTest.create(model, fold[0], fold[1])
-            cv.validation_ids << validation.id
-            cv.nr_instances += validation.nr_instances
-            cv.nr_unpredicted += validation.nr_unpredicted
-            $logger.debug "Dataset #{training_dataset.name}, Fold #{fold_nr}:  #{Time.now-t} seconds"
-          #end
+          $logger.debug "Dataset #{training_dataset.name}: Fold #{fold_nr} started"
+          t = Time.now
+          validation = TrainTest.create(model, fold[0], fold[1])
+          cv.validation_ids << validation.id
+          cv.nr_instances += validation.nr_instances
+          cv.nr_unpredicted += validation.nr_unpredicted
+          $logger.debug "Dataset #{training_dataset.name}, Fold #{fold_nr}:  #{Time.now-t} seconds"
         end
-        #Process.waitall
         cv.save
         $logger.debug "Nr unpredicted: #{cv.nr_unpredicted}"
         cv.statistics
diff --git a/lib/dataset.rb b/lib/dataset.rb
index 9611fff..41d7b5c 100644
--- a/lib/dataset.rb
+++ b/lib/dataset.rb
@@ -401,7 +401,7 @@ module OpenTox
             substance.dataset_ids << dataset.id
             substance.dataset_ids.uniq!
             substance.save
-            dataset.data_entries << data_entries.select{|row| row[0] == substance.id}
+            dataset.data_entries += data_entries.select{|row| row[0] == substance.id}
           end
           dataset.save
           dataset
@@ -433,6 +433,8 @@ module OpenTox
         if map
           values(c,feature).each { |v| dataset.add c, new_feature, map[v] }
         else
+        end
+      end
     end
     
     def transform # TODO
@@ -446,30 +448,4 @@ module OpenTox
 
   end
 
-  # Dataset for lazar predictions
-  class LazarPrediction < Dataset
-    field :creator, type: String
-    #field :prediction_feature_id, type: BSON::ObjectId
-    field :predictions, type: Hash, default: {}
-
-    # Get prediction feature
-    # @return [OpenTox::Feature]
-    def prediction_feature
-      Feature.find prediction_feature_id
-    end
-
-    def prediction compound
-    end
-
-    def probability klass
-    end
-
-    def prediction_interval
-    end
-
-    def predictions
-    end
-
-  end
-
 end
diff --git a/lib/feature.rb b/lib/feature.rb
index 50dea77..be07e7a 100644
--- a/lib/feature.rb
+++ b/lib/feature.rb
@@ -65,7 +65,7 @@ module OpenTox
     field :training_feature_id, type: BSON::ObjectId
   end
 
-  class LazarConfidenceInterval < NumericLazarPrediction
+  class LazarPredictionInterval < NumericLazarPrediction
   end
 
   class NominalSubstanceProperty < NominalFeature
diff --git a/lib/model.rb b/lib/model.rb
index 9858949..fc98e09 100644
--- a/lib/model.rb
+++ b/lib/model.rb
@@ -277,7 +277,7 @@ module OpenTox
           prediction.merge! result
           prediction[:neighbors] = neighbor_ids.collect_with_index{|id,i| {:id => id, :measurement => neighbor_dependent_variables[i], :similarity => neighbor_similarities[i]}}
           #if neighbor_similarities.max < algorithms[:similarity][:warn_min]
-            #prediction[:warnings] << "Closest neighbor has similarity < #{algorithms[:similarity][:warn_min]}. Prediction may be out of applicability domain."
+            #prediction[:warnings] << "Closest neighbor has similarity #{neighbor_similarities.max} < #{algorithms[:similarity][:warn_min]}. Prediction may be out of applicability domain."
           #end
         end
         if prediction[:warnings].empty? or threshold < algorithms[:similarity][:min] or threshold <= 0.2
@@ -328,7 +328,8 @@ module OpenTox
         elsif object.is_a? Array
           return predictions
         elsif object.is_a? Dataset
-          warning_feature = InfoFeature.find_or_create_by(:name => "Warnings")
+          d = object.copy
+          warning_feature = Warnings.find_or_create_by(:dataset_id => d.id)
           if prediction_feature.is_a? NominalBioActivity
             f = NominalLazarPrediction.find_or_create_by(:name => prediction_feature.name, :accept_values => prediction_feature.accept_values, :model_id => self.id, :training_feature_id => prediction_feature.id)
             probability_features = {}
@@ -337,17 +338,19 @@ module OpenTox
             end
           elsif prediction_feature.is_a? NumericBioActivity
             f = NumericLazarPrediction.find_or_create_by(:name => prediction_feature.name, :unit => prediction_feature.unit, :model_id => self.id, :training_feature_id => prediction_feature.id)
-            # TODO prediction interval
+            prediction_interval = {}
+            ["lower","upper"].each do |v|
+              prediction_interval[v] = LazarPredictionInterval.find_or_create_by(:name => v, :model_id => self.id, :training_feature_id => prediction_feature.id)
+            end
           end
 
-          d = Dataset.new(:name => object.name)
           # add predictions to dataset
           predictions.each do |substance_id,p|
             d.add substance_id,warning_feature,p[:warnings].join(" ") if p[:warnings]
             unless p[:value].nil?
               d.add substance_id,f,p[:value]
-              p[:probabilities].each {|name,p| d.add substance_id,probability_features[name],p}
-            # TODO prediction interval
+              p[:probabilities].each {|name,p| d.add substance_id,probability_features[name],p} if p[:probabilities]
+              p[:prediction_interval].each_with_index {|v,i| d.add substance_id, prediction_interval[i], v } if p[:prediction_interval]
             end
           end
           d.save