diff options
Diffstat (limited to 'test')
-rw-r--r-- | test/compound.rb | 15 | ||||
-rw-r--r-- | test/model-nanoparticle.rb | 2 | ||||
-rw-r--r-- | test/validation-classification.rb (renamed from test/validation.rb) | 48 | ||||
-rw-r--r-- | test/validation-nanoparticle.rb | 21 |
4 files changed, 18 insertions, 68 deletions
diff --git a/test/compound.rb b/test/compound.rb index 19f51fd..bdfb749 100644 --- a/test/compound.rb +++ b/test/compound.rb @@ -111,20 +111,9 @@ print c.sdf assert_equal 100.15888, c.molecular_weight end - def test_mg_conversions - # TODO fix! - skip - c = OpenTox::Compound.from_smiles "O" - mw = c.molecular_weight - assert_equal 18.01528, mw - assert_equal 0.8105107141417474, c.logmmol_to_mg(4.34688225631145, mw) - assert_equal 9007.64, c.mmol_to_mg(500, mw) - assert_equal 2437.9999984148976, c.logmg_to_mg(3.387033701) - end - def test_physchem c = OpenTox::Compound.from_smiles "CC(=O)CC(C)C" - assert_equal PhysChem::OPENBABEL.size, c.properties.size - assert_equal PhysChem::OPENBABEL.size, c.properties([PhysChem::OPENBABEL]).size + properties = c.calculate_properties(PhysChem.openbabel_descriptors) + assert_equal PhysChem::OPENBABEL.size, properties.size end end diff --git a/test/model-nanoparticle.rb b/test/model-nanoparticle.rb index fb81b83..6e18add 100644 --- a/test/model-nanoparticle.rb +++ b/test/model-nanoparticle.rb @@ -1,6 +1,6 @@ require_relative "setup.rb" -class NanoparticleTest < MiniTest::Test +class NanoparticleModelTest < MiniTest::Test include OpenTox::Validation def setup diff --git a/test/validation.rb b/test/validation-classification.rb index 03adf69..b71e427 100644 --- a/test/validation.rb +++ b/test/validation-classification.rb @@ -1,6 +1,6 @@ require_relative "setup.rb" -class ValidationTest < MiniTest::Test +class ValidationClassificationTest < MiniTest::Test include OpenTox::Validation # defaults @@ -13,14 +13,6 @@ class ValidationTest < MiniTest::Test assert cv.weighted_accuracy > cv.accuracy, "Weighted accuracy (#{cv.weighted_accuracy}) should be larger than accuracy (#{cv.accuracy})." end - def test_default_regression_crossvalidation - dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi_log10.csv" - model = Model::Lazar.create training_dataset: dataset - cv = RegressionCrossValidation.create model - assert cv.rmse < 1.5, "RMSE #{cv.rmse} should be smaller than 1.5, this may occur due to an unfavorable training/test set split" - assert cv.mae < 1, "MAE #{cv.mae} should be smaller than 1, this may occur due to an unfavorable training/test set split" - end - # parameters def test_classification_crossvalidation_parameters @@ -45,37 +37,6 @@ class ValidationTest < MiniTest::Test end end - def test_regression_crossvalidation_params - dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi_log10.csv" - algorithms = { - :prediction => { :method => "OpenTox::Algorithm::Regression.weighted_average" }, - :descriptors => { :type => "MACCS", }, - :similarity => {:min => 0.7} - } - model = Model::Lazar.create training_dataset: dataset, algorithms: algorithms - assert_equal algorithms[:descriptors][:type], model.algorithms[:descriptors][:type] - cv = RegressionCrossValidation.create model - cv.validation_ids.each do |vid| - model = Model::Lazar.find(Validation.find(vid).model_id) - assert_equal algorithms[:descriptors][:type], model.algorithms[:descriptors][:type] - assert_equal algorithms[:similarity][:min], model.algorithms[:similarity][:min] - refute_nil model.training_dataset_id - refute_equal dataset.id, model.training_dataset_id - end - - refute_nil cv.rmse - refute_nil cv.mae - end - - def test_physchem_regression_crossvalidation - skip # TODO: fix - training_dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi_log10.csv") - model = Model::Lazar.create(training_dataset.features.first, training_dataset, :prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression") - cv = RegressionCrossValidation.create model - refute_nil cv.rmse - refute_nil cv.mae - end - # LOO def test_classification_loo_validation @@ -88,13 +49,6 @@ class ValidationTest < MiniTest::Test assert loo.weighted_accuracy > loo.accuracy, "Weighted accuracy (#{loo.weighted_accuracy}) should be larger than accuracy (#{loo.accuracy})." end - def test_regression_loo_validation - dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi_log10.csv") - model = Model::Lazar.create training_dataset: dataset - loo = RegressionLeaveOneOut.create model - assert loo.r_squared > 0.34, "R^2 (#{loo.r_squared}) should be larger than 0.034" - end - # repeated CV def test_repeated_crossvalidation diff --git a/test/validation-nanoparticle.rb b/test/validation-nanoparticle.rb index 3692515..c5618e8 100644 --- a/test/validation-nanoparticle.rb +++ b/test/validation-nanoparticle.rb @@ -1,6 +1,6 @@ require_relative "setup.rb" -class NanoparticleTest < MiniTest::Test +class NanoparticleValidationTest < MiniTest::Test include OpenTox::Validation def setup @@ -24,8 +24,11 @@ class NanoparticleTest < MiniTest::Test def test_validate_pls_nanoparticle_model algorithms = { - :descriptors => { :types => ["P-CHEM"] }, - :prediction => {:parameters => 'pls' }, + :descriptors => { + :method => "properties", + :categories => ["P-CHEM"] + }, + :prediction => {:method => 'Algorithm::Caret.pls' }, } model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms assert_equal "pls", model.algorithms[:prediction][:parameters] @@ -39,12 +42,15 @@ class NanoparticleTest < MiniTest::Test def test_validate_proteomics_pls_nanoparticle_model algorithms = { - :descriptors => { :types => ["Proteomics"] }, - :prediction => { :parameters => 'pls' } + :descriptors => { + :method => "properties", + :categories => ["Proteomics"] + }, + :prediction => {:method => 'Algorithm::Caret.pls' }, } model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms assert_equal "pls", model.algorithms[:prediction][:parameters] - assert_equal "Algorithm::Caret.regression", model.algorithms[:prediction][:method] + assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method] cv = CrossValidation.create model p cv.rmse p cv.r_squared @@ -55,7 +61,8 @@ class NanoparticleTest < MiniTest::Test def test_validate_all_default_nanoparticle_model algorithms = { :descriptors => { - :types => ["Proteomics","P-CHEM"] + :method => "properties", + :categories => ["Proteomics","P-CHEM"] }, } model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms |