require_relative "setup.rb" class LazarExtendedTest < MiniTest::Test def test_lazar_bbrc_ham_minfreq dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"hamster_carcinogenicity.csv") model = OpenTox::Model::Lazar.create dataset, OpenTox::Algorithm::Fminer.bbrc(dataset, :min_frequency => 5) feature_dataset = OpenTox::Dataset.find model.feature_dataset_id assert_equal dataset.compounds.size, feature_dataset.compounds.size assert_equal 41, feature_dataset.features.size assert_equal 'N-C=N', feature_dataset.features.first.smarts compound = OpenTox::Compound.from_inchi("InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H") prediction = model.predict compound assert_equal "false", prediction[:value] assert_equal 0.12380952380952381, prediction[:confidence] dataset.delete model.delete feature_dataset.delete end def test_lazar_bbrc_large_ds # TODO fminer crashes with these settings skip "it seems that fminer aborts without further notice" dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"multi_cell_call_no_dup.csv") feature_dataset = OpenTox::Algorithm::Fminer.bbrc dataset#, :min_frequency => 15) model = OpenTox::Model::Lazar.create dataset, feature_dataset model.save p model.id feature_dataset = OpenTox::CalculatedDataset.find model.feature_dataset_id assert_equal dataset.compounds.size, feature_dataset.compounds.size assert_equal 52, feature_dataset.features.size assert_equal '[#17&A]-[#6&A]', feature_dataset.features.first.name compound = OpenTox::Compound.from_inchi("InChI=1S/C10H9NO2S/c1-8-2-4-9(5-3-8)13-6-10(12)11-7-14/h2-5H,6H2,1H3") prediction_dataset = model.predict compound prediction = prediction_dataset.data_entries.first assert_in_delta 0.025, prediction[:confidence], 0.001 #assert_equal 0.025885845574483608, prediction[:confidence] # with compound change in training_dataset see: # https://github.com/opentox/opentox-test/commit/0e78c9c59d087adbd4cc58bab60fb29cbe0c1da0 #assert_equal 0.02422364949075546, prediction[:confidence] dataset.delete model.delete feature_dataset.delete prediction_dataset.delete end def test_lazar_kazius t = Time.now dataset = Dataset.from_csv_file File.join(DATA_DIR,"kazius.csv") p "Dataset upload: #{Time.now-t}" t = Time.now feature_dataset = Algorithm::Fminer.bbrc(dataset, :min_frequency => 100) p "Feature mining: #{Time.now-t}" t = Time.now assert_equal feature_dataset.compounds.size, dataset.compounds.size model = Model::Lazar.create dataset, feature_dataset =begin =end #model = Model::Lazar.find('55bcf5bf7a7838381200017e') #p model.id #prediction_times = [] 2.times do compound = Compound.from_smiles("Clc1ccccc1NN") prediction = model.predict compound assert_equal "1", prediction[:value] assert_in_delta 0.019858401199860445, prediction[:confidence], 0.001 end #dataset.delete #feature_dataset.delete end end