require_relative "setup.rb" class NanomaterialValidationModelTest < MiniTest::Test def setup @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::Validation.from_enanomapper [:endpoint,:species,:source].each do |p| refute_empty validation_model[p] end 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." validation_model.delete end def test_nanomaterial_validation_model_parameters algorithms = { :descriptors => { :method => "fingerprint", :type => "MP2D", }, :similarity => { :method => "Algorithm::Similarity.tanimoto", :min => 0.1 }, :prediction => { :method => "OpenTox::Algorithm::Regression.weighted_average" }, :feature_selection => nil } 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] end end