dataset merge

3 files changed, 53 insertions, 10 deletions

diff --git a/lib/dataset.rb b/lib/dataset.rb
index 4543e42..46a83d7 100644
--- a/lib/dataset.rb
+++ b/lib/dataset.rb
@@ -94,6 +94,12 @@ module OpenTox
       features.select{|f| f._type.match("Prediction")}
     end
 
+    # Get nominal and numeric merged features
+    # @return [Array<OpenTox::NominalLazarPrediction,OpenTox::NumericLazarPrediction>]
+    def merged_features
+      features.select{|f| f._type.match("Merged")}
+    end
+
     # Writers
 
     # Add a value for a given substance and feature
@@ -425,27 +431,48 @@ module OpenTox
       end
       chunks
     end
-=begin
+
     # Merge an array of datasets 
     # @param [Array<OpenTox::Dataset>] datasets to be merged
     # @return [OpenTox::Dataset] merged dataset
-    def self.merge datasets: datasets, features: features, value_maps: value_maps, keep_original_features: keep_original_features, remove_duplicates: remove_duplicates
+    def self.merge datasets: , features: , value_maps: , keep_original_features: , remove_duplicates: 
       dataset = self.create(:source => datasets.collect{|d| d.id.to_s}.join(", "), :name => datasets.collect{|d| d.name}.uniq.join(", ")+" merged")
-      datasets.each_with_index do |d,i|
+
+      datasets.each do |d|
         dataset.data_entries += d.data_entries
         dataset.warnings += d.warnings
-      end
+      end if keep_original_features
+
       feature_classes = features.collect{|f| f.class}.uniq
+      merged_feature = nil
       if feature_classes.size == 1
-        if features.first.nominal?
-          merged_feature = MergedNominalBioActivity.find_or_create_by(:name => features.collect{|f| f.name} + " (merged)", :original_feature_id => feature.id, :transformation => map, :accept_values => map.values.sort)
-      compounds.each do |c|
-        values(c,feature).each { |v| dataset.add c, new_feature, map[v] }
+        if features.first.kind_of? NominalFeature
+          merged_feature = MergedNominalBioActivity.find_or_create_by(:name => features.collect{|f| f.name}.uniq.join(", ") + " merged", :original_feature_ids => features.collect{|f| f.id}, :transformations => value_maps)
+        else
+          merged_feature = MergedNumericBioActivity.find_or_create_by(:name => features.collect{|f| f.name} + " merged", :original_feature_ids => features.collect{|f| f.id}) # TODO, :transformations 
+        end
+      else
+        bad_request_error "Cannot merge features of different types (#{feature_classes})."
       end
+
+      accept_values = []
+      features.each_with_index do |f,i|
+        dataset.data_entries += datasets[i].data_entries.select{|de| de[1] == f.id}.collect do |de|
+          value_maps[i] ?  v = value_maps[i][de[2]] : v = de[2]
+          accept_values << v
+          [de[0],merged_feature.id,v]
+        end
+      end
+
+      if merged_feature.is_a? MergedNominalBioActivity
+        merged_feature.accept_values = accept_values.uniq.sort
+        merged_feature.save
+      end
+
+      dataset.data_entries.uniq! if remove_duplicates
       dataset.save
       dataset
     end
-=end
 
     # Change nominal feature values
     # @param [NominalFeature] Original feature
diff --git a/lib/feature.rb b/lib/feature.rb
index 50bbc42..b474398 100644
--- a/lib/feature.rb
+++ b/lib/feature.rb
@@ -34,7 +34,13 @@ module OpenTox
   end
 
   # Merged nominal biological activity
-  class MergedNominalBioActivity < NominalFeature
+  class MergedNominalBioActivity < NominalBioActivity
+    field :original_feature_ids, type: Array
+    field :transformations, type: Array
+  end
+
+  # Merged numeric biological activity
+  class MergedNumericBioActivity < NumericBioActivity
     field :original_feature_ids, type: Array
   end
 
diff --git a/lib/model.rb b/lib/model.rb
index 6d5cf7b..f50fcd7 100644
--- a/lib/model.rb
+++ b/lib/model.rb
@@ -487,6 +487,16 @@ module OpenTox
       end
 
       # TODO from_pubchem_aid
+      def self.from_dataset training_dataset: , prediction_feature: , species: , endpoint: 
+        model_validation = Model::Validation.create species: species, endpoint: endpoint
+        p "create model"
+        model = Lazar.create training_dataset: training_dataset, prediction_feature: prediction_feature
+        model_validation[:model_id] = model.id
+        p "create_crossvalidations"
+        model_validation[:repeated_crossvalidation_id] = OpenTox::Validation::RepeatedCrossValidation.create(model).id # full class name required
+        model_validation.save
+        model_validation
+      end
 
       # Create and validate a lazar model from a csv file with training data and a json file with metadata
       # @param [File] CSV file with two columns. The first line should contain either SMILES or InChI (first column) and the endpoint (second column). The first column should contain either the SMILES or InChI of the training compounds, the second column the training compounds toxic activities (qualitative or quantitative). Use -log10 transformed values for regression datasets. Add metadata to a JSON file with the same basename containing the fields "species", "endpoint", "source" and "unit" (regression only). You can find example training data at https://github.com/opentox/lazar-public-data.