diff options
Diffstat (limited to 'test/model.rb')
| -rw-r--r-- | test/model.rb | 31 |
1 files changed, 6 insertions, 25 deletions
diff --git a/test/model.rb b/test/model.rb index 563d081..02b8e73 100644 --- a/test/model.rb +++ b/test/model.rb @@ -13,7 +13,7 @@ class ModelTest < MiniTest::Test :min => 0.1 }, :prediction => { - :method => "Algorithm::Regression.caret", + :method => "Algorithm::Caret.regression", :parameters => "pls", }, :feature_selection => nil, @@ -65,7 +65,7 @@ class ModelTest < MiniTest::Test training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.mini_log10.csv") model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms assert_kind_of Model::LazarRegression, model - assert_equal "Algorithm::Regression.caret", model.algorithms[:prediction][:method] + assert_equal "Algorithm::Caret.regression", model.algorithms[:prediction][:method] assert_equal "Algorithm::Similarity.weighted_cosine", model.algorithms[:similarity][:method] assert_equal 0.1, model.algorithms[:similarity][:min] assert_equal algorithms[:descriptors], model.algorithms[:descriptors] @@ -78,7 +78,7 @@ class ModelTest < MiniTest::Test training_dataset = Dataset.where(name: "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles").first end model = Model::Lazar.create training_dataset: training_dataset - assert_equal "Algorithm::Regression.caret", model.algorithms[:prediction][:method] + assert_equal "Algorithm::Caret.regression", model.algorithms[:prediction][:method] assert_equal "rf", model.algorithms[:prediction][:parameters] assert_equal "Algorithm::Similarity.weighted_cosine", model.algorithms[:similarity][:method] prediction = model.predict training_dataset.substances[14] @@ -87,6 +87,7 @@ class ModelTest < MiniTest::Test end def test_nanoparticle_parameters + skip end def test_regression_with_feature_selection @@ -98,13 +99,14 @@ class ModelTest < MiniTest::Test training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.mini_log10.csv") model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms assert_kind_of Model::LazarRegression, model - assert_equal "Algorithm::Regression.caret", model.algorithms[:prediction][:method] + assert_equal "Algorithm::Caret.regression", model.algorithms[:prediction][:method] assert_equal "Algorithm::Similarity.tanimoto", model.algorithms[:similarity][:method] assert_equal 0.1, model.algorithms[:similarity][:min] assert_equal algorithms[:feature_selection][:method], model.algorithms[:feature_selection][:method] end def test_caret_parameters + skip end def test_default_classification @@ -153,25 +155,4 @@ class ModelTest < MiniTest::Test assert_equal 4, prediction[:neighbors].size end -=begin - def test_physchem_description - assert_equal 355, PhysChem.descriptors.size - assert_equal 15, PhysChem.openbabel_descriptors.size - assert_equal 295, PhysChem.cdk_descriptors.size - assert_equal 45, PhysChem.joelib_descriptors.size - assert_equal 310, PhysChem.unique_descriptors.size - end - - def test_physchem - assert_equal 355, PhysChem.descriptors.size - c = Compound.from_smiles "CC(=O)CC(C)C" - logP = PhysChem.find_or_create_by :name => "Openbabel.logP" - assert_equal 1.6215, logP.calculate(c) - jlogP = PhysChem.find_or_create_by :name => "Joelib.LogP" - assert_equal 3.5951, jlogP.calculate(c) - alogP = PhysChem.find_or_create_by :name => "Cdk.ALOGP.ALogP" - assert_equal 0.35380000000000034, alogP.calculate(c) - end -=end - end |