diff options
Diffstat (limited to 'test/nanoparticles.rb')
| -rw-r--r-- | test/nanoparticles.rb | 18 |
1 files changed, 12 insertions, 6 deletions
diff --git a/test/nanoparticles.rb b/test/nanoparticles.rb index f0ded2f..a2c77b5 100644 --- a/test/nanoparticles.rb +++ b/test/nanoparticles.rb @@ -2,13 +2,14 @@ require_relative "setup.rb" class NanoparticleTest < MiniTest::Test + include OpenTox::Validation def setup #Import::Enanomapper.import File.join(File.dirname(__FILE__),"data","enm") - #`mongorestore --db=development #{File.join(File.dirname(__FILE__),"..","dump","production")}` 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: "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 => "physchem_neighbors", :feature_selection_algorithm => "correlation_filter"}) @@ -21,6 +22,7 @@ class NanoparticleTest < MiniTest::Test end def test_create_model + 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: "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 => "physchem_neighbors"}) @@ -33,6 +35,7 @@ class NanoparticleTest < MiniTest::Test # TODO move to validation-statistics def test_inspect_cv + skip cv = CrossValidation.all.sort_by{|cv| cv.created_at}.last cv.correlation_plot_id = nil File.open("tmp.pdf","w+"){|f| f.puts cv.correlation_plot} @@ -63,6 +66,7 @@ class NanoparticleTest < MiniTest::Test =end end def test_inspect_worst_prediction + skip # TODO check/fix single/double neighbor prediction cv = CrossValidation.all.sort_by{|cv| cv.created_at}.last worst_predictions = cv.worst_predictions(n: 3,show_neigbors: false) @@ -88,19 +92,21 @@ class NanoparticleTest < MiniTest::Test model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_weighted_average", :neighbor_algorithm => "physchem_neighbors", :neighbor_algorithm_parameters => {:min_sim => 0.5}}) cv = RegressionCrossValidation.create model - p cv.predictions.sort_by{|sid,p| (p["value"] - p["measurements"].median).abs} + p cv + #p cv.predictions.sort_by{|sid,p| (p["value"] - p["measurements"].median).abs} p cv.rmse p cv.r_squared - File.open("tmp.pdf","w+"){|f| f.puts cv.correlation_plot} + #File.open("tmp.pdf","w+"){|f| f.puts cv.correlation_plot} refute_nil cv.r_squared refute_nil cv.rmse end def test_validate_pls_model + 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: "Net cell association", category: "TOX", unit: "mL/ug(Mg)") model = Model::LazarRegression.create(feature, training_dataset, {:prediction_algorithm => "OpenTox::Algorithm::Regression.local_physchem_regression", :neighbor_algorithm => "physchem_neighbors"}) - cv = RegressionCrossValidation.create model + cv = Validation::RegressionCrossValidation.create model p cv File.open("tmp.png","w+"){|f| f.puts cv.correlation_plot} refute_nil cv.r_squared @@ -108,16 +114,17 @@ class NanoparticleTest < MiniTest::Test end def test_export + skip Dataset.all.each do |d| puts d.to_csv end end def test_summaries + skip 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}"} @@ -125,7 +132,6 @@ class NanoparticleTest < MiniTest::Test end assert_equal 9, datasets.size =begin - skip features = Feature.all.to_a #p features.collect do |f| #f if f.category == "TOX" |