diff options
Diffstat (limited to 'lib/lazar.rb')
| -rw-r--r-- | lib/lazar.rb | 32 |
1 files changed, 16 insertions, 16 deletions
diff --git a/lib/lazar.rb b/lib/lazar.rb index f849a48..6ce19d8 100644 --- a/lib/lazar.rb +++ b/lib/lazar.rb @@ -20,9 +20,9 @@ module OpenTox # @param[Hash] REST parameters, as input by user def self.create params - lazar = OpenTox::Model::Lazar.new(File.join($model[:uri],SecureRandom.uuid), @subjectid) + lazar = OpenTox::Model::Lazar.new(File.join($model[:uri],SecureRandom.uuid)) - training_dataset = OpenTox::Dataset.new(params[:dataset_uri], @subjectid) + training_dataset = OpenTox::Dataset.new(params[:dataset_uri]) lazar.parameters << {RDF::DC.title => "training_dataset_uri", RDF::OT.paramValue => training_dataset.uri} if params[:prediction_feature] @@ -32,8 +32,8 @@ module OpenTox params[:prediction_feature] = training_dataset.features.first.uri end lazar[RDF::OT.trainingDataset] = training_dataset.uri - prediction_feature = OpenTox::Feature.new(params[:prediction_feature], @subjectid) - predicted_variable = OpenTox::Feature.find_or_create({RDF::DC.title => "#{prediction_feature.title} prediction", RDF.type => [RDF::OT.Feature, prediction_feature[RDF.type]]}, @subjectid) + prediction_feature = OpenTox::Feature.new(params[:prediction_feature]) + predicted_variable = OpenTox::Feature.find_or_create({RDF::DC.title => "#{prediction_feature.title} prediction", RDF.type => [RDF::OT.Feature, prediction_feature[RDF.type]]}) lazar[RDF::DC.title] = prediction_feature.title lazar.parameters << {RDF::DC.title => "prediction_feature_uri", RDF::OT.paramValue => prediction_feature.uri} lazar[RDF::OT.dependentVariables] = prediction_feature.uri @@ -41,7 +41,7 @@ module OpenTox bad_request_error "Unknown prediction_algorithm #{params[:prediction_algorithm]}" if params[:prediction_algorithm] and !OpenTox::Algorithm::Neighbors.respond_to?(params[:prediction_algorithm]) lazar.parameters << {RDF::DC.title => "prediction_algorithm", RDF::OT.paramValue => params[:prediction_algorithm]} if params[:prediction_algorithm] - confidence_feature = OpenTox::Feature.find_or_create({RDF::DC.title => "predicted_confidence", RDF.type => [RDF::OT.Feature, RDF::OT.NumericFeature]}, @subjectid) + confidence_feature = OpenTox::Feature.find_or_create({RDF::DC.title => "predicted_confidence", RDF.type => [RDF::OT.Feature, RDF::OT.NumericFeature]}) lazar[RDF::OT.predictedVariables] = [ predicted_variable.uri, confidence_feature.uri ] case prediction_feature.feature_type when "classification" @@ -77,12 +77,12 @@ module OpenTox lazar.parameters << {RDF::DC.title => "min_train_performance", RDF::OT.paramValue => 0.1} unless lazar.parameter_value("min_train_performance") if params[:feature_dataset_uri] - bad_request_error "Feature dataset #{params[:feature_dataset_uri]} does not exist." unless URI.accessible? params[:feature_dataset_uri], @subjectid + bad_request_error "Feature dataset #{params[:feature_dataset_uri]} does not exist." unless URI.accessible? params[:feature_dataset_uri] lazar.parameters << {RDF::DC.title => "feature_dataset_uri", RDF::OT.paramValue => params[:feature_dataset_uri]} lazar[RDF::OT.featureDataset] = params["feature_dataset_uri"] else # run feature generation algorithm - feature_dataset_uri = OpenTox::Algorithm::Generic.new(params[:feature_generation_uri], @subjectid).run(params) + feature_dataset_uri = OpenTox::Algorithm::Generic.new(params[:feature_generation_uri]).run(params) lazar.parameters << {RDF::DC.title => "feature_dataset_uri", RDF::OT.paramValue => feature_dataset_uri} lazar[RDF::OT.featureDataset] = feature_dataset_uri end @@ -91,7 +91,7 @@ module OpenTox end def predict(params) - @prediction_dataset = OpenTox::Dataset.new(nil, @subjectid) + @prediction_dataset = OpenTox::Dataset.new # set instance variables and prediction dataset parameters from parameters params.each {|k,v| self.class.class_eval { attr_accessor k.to_sym } @@ -104,9 +104,9 @@ module OpenTox instance_variable_set("@#{k}", []) } - @prediction_feature = OpenTox::Feature.new @prediction_feature_uri, @subjectid - @predicted_variable = OpenTox::Feature.new @predicted_variable_uri, @subjectid - @predicted_confidence = OpenTox::Feature.new @predicted_confidence_uri, @subjectid + @prediction_feature = OpenTox::Feature.new @prediction_feature_uri + @predicted_variable = OpenTox::Feature.new @predicted_variable_uri + @predicted_confidence = OpenTox::Feature.new @predicted_confidence_uri @prediction_dataset.metadata = { RDF::DC.title => "Lazar prediction for #{@prediction_feature.title}", RDF::DC.creator => @model_uri, @@ -115,21 +115,21 @@ module OpenTox RDF::OT.predictedVariables => [@predicted_variable_uri,@predicted_confidence_uri] } - @training_dataset = OpenTox::Dataset.new(@training_dataset_uri,@subjectid) + @training_dataset = OpenTox::Dataset.new(@training_dataset_uri) - @feature_dataset = OpenTox::Dataset.new(@feature_dataset_uri, @subjectid) + @feature_dataset = OpenTox::Dataset.new(@feature_dataset_uri) bad_request_error "No features found in feature dataset #{@feature_dataset.uri}." if @feature_dataset.features.empty? - @similarity_feature = OpenTox::Feature.find_or_create({RDF::DC.title => "#{@similarity_algorithm.capitalize} similarity", RDF.type => [RDF::OT.Feature, RDF::OT.NumericFeature]}, @subjectid) + @similarity_feature = OpenTox::Feature.find_or_create({RDF::DC.title => "#{@similarity_algorithm.capitalize} similarity", RDF.type => [RDF::OT.Feature, RDF::OT.NumericFeature]}) @prediction_dataset.features = [ @predicted_variable, @predicted_confidence, @prediction_feature, @similarity_feature ] prediction_feature_pos = @training_dataset.features.collect{|f| f.uri}.index @prediction_feature.uri if @dataset_uri - compounds = OpenTox::Dataset.new(@dataset_uri, @subjectid).compounds + compounds = OpenTox::Dataset.new(@dataset_uri).compounds else - compounds = [ OpenTox::Compound.new(@compound_uri, @subjectid) ] + compounds = [ OpenTox::Compound.new(@compound_uri) ] end @training_fingerprints = @feature_dataset.data_entries |