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require_relative "setup.rb"
class NanomaterialPredictionModelTest < MiniTest::Test
def setup
@training_dataset = Dataset.where(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles").first
unless @training_dataset
Import::Enanomapper.import File.join(File.dirname(__FILE__),"data","enm")
@training_dataset = Dataset.where(name: "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles").first
end
@prediction_feature = @training_dataset.features.select{|f| f["name"] == 'log2(Net cell association)'}.first
end
def test_default_nanomaterial_prediction_model
prediction_model = Model::NanoPrediction.create
[:endpoint,:species,:source].each do |p|
refute_empty prediction_model[p]
end
assert prediction_model.regression?
refute prediction_model.classification?
prediction_model.crossvalidations.each do |cv|
refute_nil cv.r_squared
refute_nil cv.rmse
end
nanoparticle = @training_dataset.nanoparticles[-34]
assert_includes nanoparticle.dataset_ids, @training_dataset.id
prediction = prediction_model.predict nanoparticle
refute_nil prediction[:value]
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."
prediction_model.delete
end
def test_nanomaterial_prediction_model_parameters
algorithms = {
:descriptors => {
:method => "fingerprint",
:type => "MP2D",
},
:similarity => {
:method => "Algorithm::Similarity.tanimoto",
:min => 0.1
},
:prediction => { :method => "OpenTox::Algorithm::Regression.weighted_average" },
:feature_selection => nil
}
prediction_model = Model::NanoPrediction.create algorithms: algorithms
assert prediction_model.regression?
refute prediction_model.classification?
prediction_model.crossvalidations.each do |cv|
refute_nil cv.r_squared
refute_nil cv.rmse
end
nanoparticle = @training_dataset.nanoparticles[-34]
assert_includes nanoparticle.dataset_ids, @training_dataset.id
prediction = prediction_model.predict nanoparticle
refute_nil prediction[:value]
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."
end
end
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