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require_relative "setup.rb"
class LazarFminerTest < MiniTest::Test
def test_lazar_fminer
training_dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"hamster_carcinogenicity.csv")
feature_dataset = OpenTox::Algorithm::Fminer.bbrc(:dataset => training_dataset)
#p feature_dataset
model = OpenTox::Model::Lazar.create training_dataset, feature_dataset
#feature_dataset = OpenTox::Dataset.find model.feature_dataset_id
p model
assert_equal training_dataset.compounds.size, feature_dataset.compounds.size
assert_equal 54, feature_dataset.features.size
#feature_dataset.data_entries.each do |e|
#assert_equal e.size, feature_dataset.features.size
#end
assert_equal '[#6&A]-[#6&A]-[#6&A]=[#6&A]', feature_dataset.features.first.smarts
[ {
:compound => OpenTox::Compound.from_inchi("InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H"),
:prediction => "false",
:confidence => 0.25281385281385277
},{
:compound => OpenTox::Compound.from_smiles("c1ccccc1NN"),
:prediction => "false",
:confidence => 0.3639589577089577
} ].each do |example|
prediction_dataset = model.predict :compound => example[:compound]
prediction = prediction_dataset.data_entries.first.first
confidence = prediction_dataset.data_entries.first.last
assert_equal example[:prediction], prediction
assert_equal example[:confidence], confidence
end
# make a dataset prediction
compound_dataset = OpenTox::Dataset.from_sdf File.join(DATA_DIR,"EPAFHM.mini.csv")
#assert_equal compound_dataset.uri.uri?, true
prediction = model.predict :dataset => compound_dataset
assert_equal compound_dataset.compounds, prediction.compounds
#prediction = OpenTox::Dataset.new prediction_uri
#assert_equal prediction.uri.uri?, true
# cleanup
[dataset,model,feature_dataset,compound_dataset].each{|o| o.delete}
end
end
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