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author | gebele <gebele@in-silico.ch> | 2016-12-12 09:15:48 +0000 |
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committer | gebele <gebele@in-silico.ch> | 2016-12-12 09:15:48 +0000 |
commit | da086fad5b45c0d7b59feb40d0108ac620613933 (patch) | |
tree | 7e9cf8c9332e30552ab255ee9b30e04e904977b4 /test/lazar-long.rb | |
parent | 32a16d99b51642cac8e75f90c43753d8d05ab770 (diff) | |
parent | 4570f11444bc10da88d849e9a2812e95a8933c8a (diff) |
merged development
Diffstat (limited to 'test/lazar-long.rb')
-rw-r--r-- | test/lazar-long.rb | 92 |
1 files changed, 0 insertions, 92 deletions
diff --git a/test/lazar-long.rb b/test/lazar-long.rb deleted file mode 100644 index 525b96e..0000000 --- a/test/lazar-long.rb +++ /dev/null @@ -1,92 +0,0 @@ -require_relative "setup.rb" - -class LazarExtendedTest < MiniTest::Test - - def test_lazar_bbrc_ham_minfreq - skip - dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"hamster_carcinogenicity.csv") - model = Model::LazarFminerClassification.create(dataset, :min_frequency => 5) - feature_dataset = Dataset.find model.neighbor_algorithm_parameters[:feature_dataset_id] - assert_equal dataset.compounds.size, feature_dataset.compounds.size - assert_equal model.feature_calculation_parameters, {"min_frequency"=>5} - #TODO check frequencies, features and confidence - #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 - skip - dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"multi_cell_call_no_dup.csv") - model = Model::LazarFminerClassification.create dataset - feature_dataset = Dataset.find model.neighbor_algorithm_parameters[:feature_dataset_id] - model.save - p model.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 = model.predict compound - assert_equal "1", prediction[:value] - #p prediction - #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 - end - - def test_lazar_fminer_kazius - skip - t = Time.now - dataset = Dataset.from_csv_file File.join(DATA_DIR,"kazius.csv") - p "Dataset upload: #{Time.now-t}" - t = Time.now - model = Model::LazarFminerClassification.create(dataset, :min_frequency => 100) - p "Feature mining: #{Time.now-t}" - t = Time.now - feature_dataset = Dataset.find model.neighbor_algorithm_parameters[:feature_dataset_id] - assert_equal feature_dataset.compounds.size, dataset.compounds.size - #model = Model::Lazar.find('55bcf5bf7a7838381200017e') - #p model.id - #prediction_times = [] - 2.times do - compound = Compound.from_smiles("Clc1ccccc1NN") - prediction = model.predict compound - p prediction - #assert_equal "1", prediction[:value] - #assert_in_delta 0.019858401199860445, prediction[:confidence], 0.001 - end - #dataset.delete - #feature_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 - model = Model::LazarClassification.create(dataset) - p "Feature mining: #{Time.now-t}" - t = Time.now - 2.times do - compound = Compound.from_smiles("Clc1ccccc1NN") - prediction = model.predict compound - #p prediction - assert_equal "1", prediction[:value] - #assert_in_delta 0.019858401199860445, prediction[:confidence], 0.001 - end - dataset.delete - end - -end |