module OpenTox class Validation field :model_id, type: BSON::ObjectId field :prediction_dataset_id, type: BSON::ObjectId field :crossvalidation_id, type: BSON::ObjectId field :test_dataset_id, type: BSON::ObjectId field :nr_instances, type: Integer field :nr_unpredicted, type: Integer field :predictions, type: Array def prediction_dataset Dataset.find prediction_dataset_id end def test_dataset Dataset.find test_dataset_id end def model Model::Lazar.find model_id end def self.create model, training_set, test_set, crossvalidation=nil atts = model.attributes.dup # do not modify attributes from original model atts["_id"] = BSON::ObjectId.new atts[:training_dataset_id] = training_set.id validation_model = model.class.create training_set, atts validation_model.save test_set_without_activities = Dataset.new(:compound_ids => test_set.compound_ids) # just to be sure that activities cannot be used prediction_dataset = validation_model.predict test_set_without_activities predictions = [] nr_unpredicted = 0 activities = test_set.data_entries.collect{|de| de.first} prediction_dataset.data_entries.each_with_index do |de,i| if de[0] and de[1] and de[1].numeric? activity = activities[i] prediction = de.first confidence = de[1] predictions << [prediction_dataset.compound_ids[i], activity, prediction, de[1]] else nr_unpredicted += 1 end end validation = self.new( :model_id => validation_model.id, :prediction_dataset_id => prediction_dataset.id, :test_dataset_id => test_set.id, :nr_instances => test_set.compound_ids.size, :nr_unpredicted => nr_unpredicted, :predictions => predictions#.sort{|a,b| p a; b[3] <=> a[3]} # sort according to confidence ) validation.crossvalidation_id = crossvalidation.id if crossvalidation validation.save validation end end class ClassificationValidation < Validation end class RegressionValidation < Validation end end