diff options
Diffstat (limited to 'test/nanoparticles.rb')
-rw-r--r-- | test/nanoparticles.rb | 23 |
1 files changed, 22 insertions, 1 deletions
diff --git a/test/nanoparticles.rb b/test/nanoparticles.rb index 46c6620..7308a83 100644 --- a/test/nanoparticles.rb +++ b/test/nanoparticles.rb @@ -1,8 +1,14 @@ require_relative "setup.rb" + class NanoparticleTest < MiniTest::Test + def setup + `mongorestore --db=development #{File.join(File.dirname(__FILE__),"..","dump","production")}` + end + def test_import + skip dataset_ids = Import::Enanomapper.import assert_operator Nanoparticle.count , :>, 570, "Only #{Nanoparticle.count} nanoparticles imported" assert_operator dataset_ids.size, :>, 8, "Only #{dataset_ids.size} bundles imported" @@ -17,6 +23,7 @@ class NanoparticleTest < MiniTest::Test end def test_summaries + skip features = Feature.all.to_a #p features.collect do |f| #f if f.category == "TOX" @@ -51,6 +58,18 @@ class NanoparticleTest < MiniTest::Test end end + def test_create_model_with_feature_selection + 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"}) + nanoparticle = training_dataset.nanoparticles[-34] + #p nanoparticle.neighbors + prediction = model.predict nanoparticle + p prediction + #p prediction + refute_nil prediction[:value] + end + def test_create_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: "7.99 Toxicity (other) ICP-AES", category: "TOX", unit: "mL/ug(Mg)") @@ -66,7 +85,9 @@ class NanoparticleTest < MiniTest::Test 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: "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_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 end |