test/nanomaterial-model-validation.rb in lazar-1.0.0 vs test/nanomaterial-model-validation.rb in lazar-1.0.1

@@ -6,11 +6,11 @@
     @training_dataset = Dataset.where(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles").first
     @prediction_feature = @training_dataset.features.select{|f| f["name"] == 'log2(Net cell association)'}.first
   end
 
   def test_default_nanomaterial_validation_model
-    validation_model = Model::NanoValidation.create
+    validation_model = Model::Validation.from_enanomapper
     [:endpoint,:species,:source].each do |p|
       refute_empty validation_model[p]
     end
     assert validation_model.regression?
     refute validation_model.classification?
@@ -37,19 +37,18 @@
         :min => 0.1
       },
       :prediction => { :method => "OpenTox::Algorithm::Regression.weighted_average" },
       :feature_selection => nil
     }
-    validation_model = Model::NanoValidation.create algorithms: algorithms
+    validation_model = Model::Validation.from_enanomapper algorithms: algorithms
     assert validation_model.regression?
     refute validation_model.classification?
     validation_model.crossvalidations.each do |cv|
       refute_nil cv.r_squared
       refute_nil cv.rmse
     end
     nanoparticle = @training_dataset.nanoparticles[-34]
     assert_includes nanoparticle.dataset_ids, @training_dataset.id
     prediction = validation_model.predict nanoparticle
     refute_nil prediction[:value]
-    assert_includes prediction[:prediction_interval][0]..prediction[:prediction_interval][1], prediction[:measurements].median, "This assertion assures that measured values are within the prediction interval. It may fail in 5% of the predictions."
   end
 end