diff options
Diffstat (limited to 'test/nanoparticles.rb')
| -rw-r--r-- | test/nanoparticles.rb | 36 |
1 files changed, 23 insertions, 13 deletions
diff --git a/test/nanoparticles.rb b/test/nanoparticles.rb index 897552d..1cd1ff0 100644 --- a/test/nanoparticles.rb +++ b/test/nanoparticles.rb @@ -9,10 +9,9 @@ class NanoparticleTest < MiniTest::Test end def test_create_model_with_feature_selection - skip training_dataset = Dataset.find_or_create_by(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles") - feature = Feature.find_or_create_by(name: "7.99 Toxicity (other) ICP-AES", category: "TOX", unit: "mL/ug(Mg)") - model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression", :neighbor_algorithm => "nanoparticle_neighbors"}) + feature = Feature.find_or_create_by(name: "Net cell association", category: "TOX", unit: "mL/ug(Mg)") + model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average", :neighbor_algorithm => "nanoparticle_neighbors", :feature_selection_algorithm => "correlation_filter"}) nanoparticle = training_dataset.nanoparticles[-34] #p nanoparticle.neighbors prediction = model.predict nanoparticle @@ -23,45 +22,55 @@ class NanoparticleTest < MiniTest::Test def test_create_model training_dataset = Dataset.find_or_create_by(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles") - #p training_dataset.nanoparticles.size feature = Feature.find_or_create_by(name: "Net cell association", category: "TOX", unit: "mL/ug(Mg)") model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average", :neighbor_algorithm => "nanoparticle_neighbors"}) - #model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression", :neighbor_algorithm => "nanoparticle_neighbors"}) nanoparticle = training_dataset.nanoparticles[-34] prediction = model.predict nanoparticle - p prediction refute_nil prediction[:value] + assert_includes nanoparticle.dataset_ids, training_dataset.id + model.delete end def test_validate_model training_dataset = Dataset.find_or_create_by(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles") feature = Feature.find_or_create_by(name: "Net cell association", category: "TOX", unit: "mL/ug(Mg)") - #feature = Feature.find_or_create_by(name: "7.99 Toxicity (other) ICP-AES", category: "TOX", unit: "mL/ug(Mg)") - model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average", :neighbor_algorithm => "nanoparticle_neighbors"}) - p model + model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average", :neighbor_algorithm => "nanoparticle_neighbors", :neighbor_algorithm_parameters => {:min_sim => 0.5}}) cv = RegressionCrossValidation.create model p cv + File.open("tmp.png","w+"){|f| f.puts cv.correlation_plot} + refute_nil cv.r_squared + refute_nil cv.rmse end def test_validate_pls_model training_dataset = Dataset.find_or_create_by(:name => "Protein Corona Fingerprinting Predicts the Cellular Interaction of Gold and Silver Nanoparticles") feature = Feature.find_or_create_by(name: "Net cell association", category: "TOX", unit: "mL/ug(Mg)") - #feature = Feature.find_or_create_by(name: "7.99 Toxicity (other) ICP-AES", category: "TOX", unit: "mL/ug(Mg)") model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression", :neighbor_algorithm => "nanoparticle_neighbors"}) - #model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average", :neighbor_algorithm => "nanoparticle_neighbors"}) - p model cv = RegressionCrossValidation.create model p cv + File.open("tmp.png","w+"){|f| f.puts cv.correlation_plot} + refute_nil cv.r_squared + refute_nil cv.rmse end def test_export - skip Dataset.all.each do |d| puts d.to_csv end end def test_summaries + datasets = Dataset.all + datasets = datasets.select{|d| !d.name.nil?} + datasets.each do |d| + p d.name + + #p d.features.select{|f| f.name.match (/Total/)} + #p d.features.collect{|f| "#{f.name} #{f.unit} #{f.conditions}"} + p d.features.uniq.collect{|f| f.name} + end + assert_equal 9, datasets.size +=begin skip features = Feature.all.to_a #p features.collect do |f| @@ -83,6 +92,7 @@ class NanoparticleTest < MiniTest::Test #pccounts.each{|e,n| p Feature.find(e),n if n > 100} #p toxcounts.collect{|e,n| Feature.find(e).name if n > 1}.uniq toxcounts.each{|e,n| p Feature.find(e),n if n > 100} +=end end |