diff options
Diffstat (limited to 'test')
| -rw-r--r-- | test/dataset.rb | 2 | ||||
| -rw-r--r-- | test/feature.rb | 10 | ||||
| -rw-r--r-- | test/model-classification.rb | 8 | ||||
| -rw-r--r-- | test/model-regression.rb | 28 | ||||
| -rw-r--r-- | test/model-validation.rb | 2 | ||||
| -rw-r--r-- | test/setup.rb | 2 | ||||
| -rw-r--r-- | test/validation-classification.rb | 2 | ||||
| -rw-r--r-- | test/validation-regression.rb | 2 |
8 files changed, 30 insertions, 26 deletions
diff --git a/test/dataset.rb b/test/dataset.rb index e91e65a..055a029 100644 --- a/test/dataset.rb +++ b/test/dataset.rb @@ -160,7 +160,7 @@ class DatasetTest < MiniTest::Test if v.numeric? assert_equal v.to_f, serialized[inchi][i].to_f else - assert_equal v, serialized[inchi][i] + assert_equal v.to_s, serialized[inchi][i].to_s end end diff --git a/test/feature.rb b/test/feature.rb index 40edb9f..85ce588 100644 --- a/test/feature.rb +++ b/test/feature.rb @@ -57,20 +57,20 @@ class FeatureTest < MiniTest::Test def test_physchem_description assert_equal 346, PhysChem.descriptors.size assert_equal 15, PhysChem.openbabel_descriptors.size - assert_equal 295, PhysChem.cdk_descriptors.size + assert_equal 286, PhysChem.cdk_descriptors.size assert_equal 45, PhysChem.joelib_descriptors.size - assert_equal 310, PhysChem.unique_descriptors.size + assert_equal 309, PhysChem.unique_descriptors.size end def test_physchem assert_equal 346, 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) + assert_equal 1.6215, c.calculate_properties([logP]).first jlogP = PhysChem.find_or_create_by :name => "Joelib.LogP" - assert_equal 3.5951, jlogP.calculate(c) + assert_equal 3.5951, c.calculate_properties([jlogP]).first alogP = PhysChem.find_or_create_by :name => "Cdk.ALOGP.ALogP" - assert_equal 0.35380000000000034, alogP.calculate(c) + assert_equal 0.35380000000000034, c.calculate_properties([alogP]).first end end diff --git a/test/model-classification.rb b/test/model-classification.rb index 1424f6a..f75598b 100644 --- a/test/model-classification.rb +++ b/test/model-classification.rb @@ -46,12 +46,14 @@ class LazarClassificationTest < MiniTest::Test assert_equal compound_dataset.compounds, prediction_dataset.compounds cid = prediction_dataset.compounds[7].id.to_s - assert_equal "Could not find similar substances with experimental data in the training dataset.", prediction_dataset.predictions[cid][:warning] + assert_equal "Could not find similar substances with experimental data in the training dataset.", prediction_dataset.predictions[cid][:warnings][0] + expectations = ["Cannot create prediction: Only one similar compound in the training set.", + "Could not find similar substances with experimental data in the training dataset."] prediction_dataset.predictions.each do |cid,pred| - assert_equal "Could not find similar substances with experimental data in the training dataset.", pred[:warning] if pred[:value].nil? + assert_includes expectations, pred[:warnings][0] if pred[:value].nil? end cid = Compound.from_smiles("CCOC(=O)N").id.to_s - assert_match "excluded", prediction_dataset.predictions[cid][:warning] + assert_match "excluded", prediction_dataset.predictions[cid][:info] # cleanup [training_dataset,model,compound_dataset,prediction_dataset].each{|o| o.delete} end diff --git a/test/model-regression.rb b/test/model-regression.rb index 86b927c..5903e88 100644 --- a/test/model-regression.rb +++ b/test/model-regression.rb @@ -10,21 +10,21 @@ class LazarRegressionTest < MiniTest::Test }, :similarity => { :method => "Algorithm::Similarity.tanimoto", - :min => 0.1 + :min => 0.5 }, :prediction => { - :method => "Algorithm::Caret.pls", + :method => "Algorithm::Caret.rf", }, :feature_selection => nil, } - training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi_log10.csv") + training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM_log10.csv") model = Model::Lazar.create training_dataset: training_dataset assert_kind_of Model::LazarRegression, model assert_equal algorithms, model.algorithms - substance = training_dataset.substances[10] + substance = training_dataset.substances[145] prediction = model.predict substance 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." - substance = Compound.from_smiles "NC(=O)OCCC" + substance = Compound.from_smiles "c1ccc(cc1)Oc1ccccc1" prediction = model.predict substance refute_nil prediction[:value] refute_nil prediction[:prediction_interval] @@ -59,8 +59,8 @@ class LazarRegressionTest < MiniTest::Test model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms compound = Compound.from_smiles "CCCSCCSCC" prediction = model.predict compound - assert_equal 4, prediction[:neighbors].size - assert_equal 1.37, prediction[:value].round(2) + assert_equal 3, prediction[:neighbors].size + assert prediction[:value].round(2) > 1.37, "Prediction value (#{prediction[:value].round(2)}) should be larger than 1.37." end def test_local_physchem_regression @@ -112,12 +112,12 @@ class LazarRegressionTest < MiniTest::Test :method => "Algorithm::Similarity.cosine", } } - training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.mini_log10.csv") + training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi_log10.csv") model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms assert_kind_of Model::LazarRegression, model - assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method] + assert_equal "Algorithm::Caret.rf", model.algorithms[:prediction][:method] assert_equal "Algorithm::Similarity.cosine", model.algorithms[:similarity][:method] - assert_equal 0.1, model.algorithms[:similarity][:min] + assert_equal 0.5, model.algorithms[:similarity][:min] algorithms[:descriptors].delete :features assert_equal algorithms[:descriptors], model.algorithms[:descriptors] prediction = model.predict training_dataset.substances[10] @@ -130,14 +130,14 @@ class LazarRegressionTest < MiniTest::Test :method => "Algorithm::FeatureSelection.correlation_filter", }, } - training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.mini_log10.csv") + training_dataset = Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM_log10.csv") model = Model::Lazar.create training_dataset: training_dataset, algorithms: algorithms assert_kind_of Model::LazarRegression, model - assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method] + assert_equal "Algorithm::Caret.rf", model.algorithms[:prediction][:method] assert_equal "Algorithm::Similarity.tanimoto", model.algorithms[:similarity][:method] - assert_equal 0.1, model.algorithms[:similarity][:min] + assert_equal 0.5, model.algorithms[:similarity][:min] assert_equal algorithms[:feature_selection][:method], model.algorithms[:feature_selection][:method] - prediction = model.predict training_dataset.substances[10] + prediction = model.predict training_dataset.substances[145] refute_nil prediction[:value] end diff --git a/test/model-validation.rb b/test/model-validation.rb index 83986d6..9304232 100644 --- a/test/model-validation.rb +++ b/test/model-validation.rb @@ -12,7 +12,7 @@ class ValidationModelTest < MiniTest::Test m.crossvalidations.each do |cv| assert cv.accuracy > 0.74, "Crossvalidation accuracy (#{cv.accuracy}) should be larger than 0.75. This may happen due to an unfavorable training/test set split." end - prediction = m.predict Compound.from_smiles("CCCC(NN)C") + prediction = m.predict Compound.from_smiles("OCC(CN(CC(O)C)N=O)O") assert_equal "true", prediction[:value] m.delete end diff --git a/test/setup.rb b/test/setup.rb index 40c8ebf..c1cddfb 100644 --- a/test/setup.rb +++ b/test/setup.rb @@ -3,6 +3,8 @@ require 'minitest/autorun' require_relative '../lib/lazar.rb' #require 'lazar' include OpenTox +#$mongo.database.drop +#$gridfs = $mongo.database.fs # recreate GridFS indexes TEST_DIR ||= File.expand_path(File.dirname(__FILE__)) DATA_DIR ||= File.join(TEST_DIR,"data") training_dataset = Dataset.where(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles").first diff --git a/test/validation-classification.rb b/test/validation-classification.rb index fb4c3e7..ce06063 100644 --- a/test/validation-classification.rb +++ b/test/validation-classification.rb @@ -47,7 +47,7 @@ class ValidationClassificationTest < MiniTest::Test dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv" model = Model::Lazar.create training_dataset: dataset loo = ClassificationLeaveOneOut.create model - assert_equal 14, loo.nr_unpredicted + assert_equal 24, loo.nr_unpredicted refute_empty loo.confusion_matrix assert loo.accuracy > 0.77 assert loo.weighted_accuracy > loo.accuracy, "Weighted accuracy (#{loo.weighted_accuracy}) should be larger than accuracy (#{loo.accuracy})." diff --git a/test/validation-regression.rb b/test/validation-regression.rb index 01ed644..c5ad312 100644 --- a/test/validation-regression.rb +++ b/test/validation-regression.rb @@ -84,7 +84,7 @@ class ValidationRegressionTest < MiniTest::Test repeated_cv = RepeatedCrossValidation.create model repeated_cv.crossvalidations.each do |cv| assert cv.r_squared > 0.34, "R^2 (#{cv.r_squared}) should be larger than 0.034" - assert_operator cv.accuracy, :>, 0.7, "model accuracy < 0.7, this may happen by chance due to an unfavorable training/test set split" + assert cv.rmse < 0.5, "RMSE (#{cv.rmse}) should be smaller than 0.5" end end |