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require_relative "setup.rb"
class LazarExtendedTest < MiniTest::Test
def test_lazar_bbrc_ham_minfreq
dataset = OpenTox::MeasuredDataset.new
dataset.upload File.join(DATA_DIR,"hamster_carcinogenicity.csv")
model = OpenTox::Model::Lazar.create OpenTox::Algorithm::Fminer.bbrc(dataset, :min_frequency => 5)
feature_dataset = OpenTox::CalculatedDataset.find model.feature_dataset_id
assert_equal dataset.compounds.size, feature_dataset.compounds.size
assert_equal 41, feature_dataset.features.size
assert_equal '[#7&A]-[#6&A]=[#7&A]', feature_dataset.features.first.title
compound = OpenTox::Compound.from_inchi("InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H")
prediction_dataset = model.predict :compound => compound
prediction = prediction_dataset.data_entries.first
assert_equal "false", prediction.first
assert_equal 0.12380952380952381, prediction.last
dataset.delete
model.delete
feature_dataset.delete
prediction_dataset.delete
end
def test_lazar_bbrc_large_ds
# TODO fminer crashes with these settings
dataset = OpenTox::MeasuredDataset.new
dataset.upload File.join(DATA_DIR,"multi_cell_call_no_dup.csv")
feature_dataset = OpenTox::Algorithm::Fminer.bbrc(:dataset => dataset)#, :min_frequency => 15)
model = OpenTox::Model::Lazar.create 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.title
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 => 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
dataset = Dataset.from_csv_file File.join(DATA_DIR,"kazius.csv")
feature_dataset = Algorithm::Fminer.bbrc(dataset, :min_frequency => 100)
assert_equal feature_dataset.compounds.size, dataset.compounds.size
model = Model::Lazar.create dataset, feature_dataset
#model = Model::Lazar.find('55b8e9c07a78383f6700017e')
p model.id
#prediction_times = []
2.times do
compound = Compound.from_smiles("Clc1ccccc1NN")
prediction = model.predict :compound => compound
p prediction.data_entries
assert_equal "1", prediction.data_entries.first.first
assert_in_delta 0.019858401199860445, prediction.data_entries.first.last, 0.001
end
#dataset.delete
#feature_dataset.delete
end
end
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