diff options
Diffstat (limited to 'lib/model.rb')
| -rw-r--r-- | lib/model.rb | 30 |
1 files changed, 12 insertions, 18 deletions
diff --git a/lib/model.rb b/lib/model.rb index 44b36e6..0d2354f 100644 --- a/lib/model.rb +++ b/lib/model.rb @@ -48,7 +48,7 @@ module OpenTox self end - def predict object, use_database_values=true + def predict object t = Time.now at = Time.now @@ -79,31 +79,21 @@ module OpenTox # remove neighbors without prediction_feature # check for database activities (neighbors may include query compound) database_activities = nil + prediction = {} if neighbors.collect{|n| n["_id"]}.include? compound.id database_activities = neighbors.select{|n| n["_id"] == compound.id}.first["features"][prediction_feature.id.to_s] + prediction[:database_activities] = database_activities + prediction[:warning] = "#{database_activities.size} structures have been removed from neighbors, because they have the same structure as the query compound." neighbors.delete_if{|n| n["_id"] == compound.id} end neighbors.delete_if{|n| n['features'].empty? or n['features'][prediction_feature.id.to_s] == [nil] } if neighbors.empty? - prediction = {:value => nil,:confidence => nil,:warning => "Cound not find similar compounds."} + prediction.merge!({:value => nil,:confidence => nil,:warning => "Could not find similar compounds with experimental data in the training dataset."}) else - prediction = Algorithm.run(prediction_algorithm, compound, {:neighbors => neighbors,:training_dataset_id=> training_dataset.id,:prediction_feature_id => prediction_feature.id}) + prediction.merge!(Algorithm.run(prediction_algorithm, compound, {:neighbors => neighbors,:training_dataset_id=> training_dataset.id,:prediction_feature_id => prediction_feature.id})) end - prediction[:database_activities] = database_activities predictions << prediction - -=begin -# TODO scaled dataset for physchem - p neighbor_algorithm_parameters - p (neighbor_algorithm_parameters["feature_dataset_id"]) - d = Dataset.find(neighbor_algorithm_parameters["feature_dataset_id"]) - p d - p d.class - if neighbor_algorithm_parameters["feature_dataset_id"] and Dataset.find(neighbor_algorithm_parameters["feature_dataset_id"]).kind_of? ScaledDataset - p "SCALED" - end -=end end # serialize result @@ -116,6 +106,8 @@ module OpenTox return predictions when "OpenTox::Dataset" # prepare prediction dataset + measurement_feature = prediction_feature + prediction_feature = OpenTox::NumericFeature.find_or_create_by( "name" => measurement_feature.name + " (Prediction)" ) prediction_dataset = LazarPrediction.new( :name => "Lazar prediction for #{prediction_feature.name}", :creator => __FILE__, @@ -125,9 +117,11 @@ module OpenTox confidence_feature = OpenTox::NumericFeature.find_or_create_by( "name" => "Prediction confidence" ) # TODO move into warnings field warning_feature = OpenTox::NominalFeature.find_or_create_by("name" => "Warnings") - prediction_dataset.features = [ prediction_feature, confidence_feature, warning_feature ] + prediction_dataset.features = [ prediction_feature, confidence_feature, measurement_feature, warning_feature ] prediction_dataset.compounds = compounds - prediction_dataset.data_entries = predictions.collect{|p| [p[:value], p[:database_activities] ? "measured" : p[:confidence] , p[:warning]]} + #prediction_dataset.data_entries = predictions.collect{|p| [p[:value], p[:database_activities] ? "measured" : p[:confidence] , p[:warning]]} + # TODO fix dataset measurements + prediction_dataset.data_entries = predictions.collect{|p| [p[:value], p[:confidence] , p[:dataset_activities].to_s, p[:warning]]} prediction_dataset.save_all return prediction_dataset end |