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authorhelma@in-silico.ch <helma@in-silico.ch>2018-10-12 21:58:36 +0200
committerhelma@in-silico.ch <helma@in-silico.ch>2018-10-12 21:58:36 +0200
commit9d17895ab9e8cd31e0f32e8e622e13612ea5ff77 (patch)
treed6984f0bd81679228d0dfd903aad09c7005f1c4c /test/model-nanoparticle.rb~
parentde763211bd2b6451e3a8dc20eb95a3ecf72bef17 (diff)
validation statistic fixes
Diffstat (limited to 'test/model-nanoparticle.rb~')
-rw-r--r--test/model-nanoparticle.rb~135
1 files changed, 135 insertions, 0 deletions
diff --git a/test/model-nanoparticle.rb~ b/test/model-nanoparticle.rb~
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+++ b/test/model-nanoparticle.rb~
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+require_relative "setup.rb"
+
+class NanoparticleModelTest < MiniTest::Test
+ include OpenTox::Validation
+
+ def setup
+ @training_dataset = Dataset.where(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles").first
+ @prediction_feature = @training_dataset.features.select{|f| f["name"] == 'log2(Net cell association)'}.first
+ end
+
+ def test_core_coating_source_uris
+ @training_dataset.nanoparticles.each do |np|
+ refute_nil np.core.source
+ np.coating.each{|c| refute_nil c.source}
+ end
+ end
+
+ def test_nanoparticle_model
+ assert true, @prediction_feature.measured
+ model = Model::Lazar.create training_dataset: @training_dataset, prediction_feature: @prediction_feature
+ refute_empty model.dependent_variables
+ refute_empty model.descriptor_ids
+ refute_empty model.independent_variables
+ assert_equal "Algorithm::Caret.rf", model.algorithms[:prediction][:method]
+ assert_equal "Algorithm::Similarity.weighted_cosine", model.algorithms[:similarity][:method]
+ nanoparticle = @training_dataset.nanoparticles[-34]
+ assert_includes nanoparticle.dataset_ids, @training_dataset.id
+ 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.predict @training_dataset.substances[14]
+ 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."
+ model.delete
+ end
+
+ def test_nanoparticle_fingerprint_model
+ assert true, @prediction_feature.measured
+ algorithms = {
+ :descriptors => {
+ :method => "fingerprint",
+ :type => "MP2D",
+ },
+ :similarity => {
+ :method => "Algorithm::Similarity.tanimoto",
+ :min => 0.1
+ },
+ :feature_selection => nil
+ }
+ model = Model::Lazar.create training_dataset: @training_dataset, prediction_feature: @prediction_feature, algorithms: algorithms
+ refute_empty model.dependent_variables
+ refute_empty model.descriptor_ids
+ refute_empty model.independent_variables
+ assert_equal "Algorithm::Caret.rf", model.algorithms[:prediction][:method]
+ assert_equal "Algorithm::Similarity.tanimoto", model.algorithms[:similarity][:method]
+ assert_nil model.algorithms[:descriptors][:categories]
+ nanoparticle = @training_dataset.nanoparticles[-34]
+ assert_includes nanoparticle.dataset_ids, @training_dataset.id
+ 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.predict @training_dataset.substances[14]
+ 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."
+ model.delete
+ end
+
+ def test_nanoparticle_fingerprint_model_with_feature_selection
+ assert true, @prediction_feature.measured
+ algorithms = {
+ :descriptors => {
+ :method => "fingerprint",
+ :type => "MP2D",
+ },
+ :similarity => {
+ :method => "Algorithm::Similarity.tanimoto",
+ :min => 0.1
+ },
+ }
+ model = Model::Lazar.create training_dataset: @training_dataset, prediction_feature: @prediction_feature, algorithms: algorithms
+ refute_empty model.algorithms[:feature_selection]
+ refute_empty model.dependent_variables
+ refute_empty model.descriptor_ids
+ refute_empty model.independent_variables
+ assert_equal "Algorithm::Caret.rf", model.algorithms[:prediction][:method]
+ assert_equal "Algorithm::Similarity.tanimoto", model.algorithms[:similarity][:method]
+ nanoparticle = @training_dataset.nanoparticles[-34]
+ assert_includes nanoparticle.dataset_ids, @training_dataset.id
+ 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.predict @training_dataset.substances[14]
+ 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."
+ model.delete
+ end
+
+ def test_nanoparticle_calculated_properties_model
+ skip "Nanoparticle calculate_properties similarity not yet implemented"
+ assert true, @prediction_feature.measured
+ algorithms = {
+ :descriptors => {
+ :method => "calculate_properties",
+ :features => PhysChem.openbabel_descriptors,
+ },
+ :similarity => {
+ :method => "Algorithm::Similarity.weighted_cosine",
+ :min => 0.5
+ },
+ :prediction => {
+ :method => "Algorithm::Regression.weighted_average",
+ },
+ }
+ model = Model::Lazar.create training_dataset: @training_dataset, prediction_feature: @prediction_feature, algorithms: algorithms
+ refute_empty model.dependent_variables
+ refute_empty model.descriptor_ids
+ refute_empty model.independent_variables
+ assert_equal "Algorithm::Caret.rf", model.algorithms[:prediction][:method]
+ assert_equal "Algorithm::Similarity.weighted", model.algorithms[:similarity][:method]
+ nanoparticle = @training_dataset.nanoparticles[-34]
+ assert_includes nanoparticle.dataset_ids, @training_dataset.id
+ 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.predict @training_dataset.substances[14]
+ 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."
+ model.delete
+ end
+
+ def test_import_ld
+ skip # Ambit JSON-LD export defunct
+ dataset_ids = Import::Enanomapper.import_ld
+ end
+end