model tests separated and cleaned

1 files changed, 0 insertions, 86 deletions

diff --git a/test/nanoparticles.rb b/test/nanoparticles.rb
deleted file mode 100644
index 9a67e63..0000000
--- a/test/nanoparticles.rb
+++ /dev/null
@@ -1,86 +0,0 @@
-require_relative "setup.rb"
-
-class NanoparticleTest  < 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
-    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_nanoparticle_model
-    model = Model::Lazar.create training_dataset: @training_dataset, prediction_feature: @prediction_feature
-    nanoparticle = @training_dataset.nanoparticles[-34]
-    prediction = model.predict nanoparticle
-    refute_nil prediction[:value]
-    assert_includes nanoparticle.dataset_ids, @training_dataset.id
-    assert true, @prediction_feature.measured
-    model.delete
-  end
-
-  # validations
-
-  def test_validate_default_nanoparticle_model
-    model = Model::Lazar.create training_dataset: @training_dataset, prediction_feature: @prediction_feature
-    cv = CrossValidation.create model
-    p cv.rmse
-    p cv.r_squared
-    #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_nanoparticle_model
-    algorithms = {
-      :descriptors => { :types => ["P-CHEM"] },
-      :prediction => {:parameters => 'pls' },
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    assert_equal "pls", model.algorithms[:prediction][:parameters]
-    assert_equal "Algorithm::Caret.regression", model.algorithms[:prediction][:method]
-    cv = CrossValidation.create model
-    p cv.rmse
-    p cv.r_squared
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-  def test_validate_proteomics_pls_nanoparticle_model
-    algorithms = {
-      :descriptors => { :types => ["Proteomics"] },
-      :prediction => { :parameters => 'pls' }
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    assert_equal "pls", model.algorithms[:prediction][:parameters]
-    assert_equal "Algorithm::Caret.regression", model.algorithms[:prediction][:method]
-    cv = CrossValidation.create model
-    p cv.rmse
-    p cv.r_squared
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-  def test_validate_all_default_nanoparticle_model
-    algorithms = {
-      :descriptors => {
-        :types => ["Proteomics","P-CHEM"]
-      },
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    cv = CrossValidation.create model
-    p cv.rmse
-    p cv.r_squared
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-
-  def test_import_ld
-    skip # Ambit JSON-LD export defunct
-    dataset_ids = Import::Enanomapper.import_ld
-  end
-end