validation statistic fixes

1 files changed, 0 insertions, 133 deletions

diff --git a/test/validation-nanoparticle.rb b/test/validation-nanoparticle.rb
deleted file mode 100644
index 0c7d355..0000000
--- a/test/validation-nanoparticle.rb
+++ /dev/null
@@ -1,133 +0,0 @@
-require_relative "setup.rb"
-
-class NanoparticleValidationTest  < 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_validate_default_nanoparticle_model
-    model = Model::Lazar.create training_dataset: @training_dataset, prediction_feature: @prediction_feature
-    cv = CrossValidation.create model
-    p cv.id
-    #File.open("tmp.pdf","w+"){|f| f.puts cv.correlation_plot format:"pdf"}
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-  def test_validate_pls_pchem_model
-    algorithms = {
-      :descriptors => {
-        :method => "properties",
-        :categories => ["P-CHEM"]
-      },
-      :prediction => {:method => 'Algorithm::Caret.pls' },
-      :feature_selection => {
-        :method => "Algorithm::FeatureSelection.correlation_filter",
-      },
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method]
-    cv = CrossValidation.create model
-    p cv.id
-    #File.open("tmp2.pdf","w+"){|f| f.puts cv.correlation_plot format:"pdf"}
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-=begin
-  def test_validate_proteomics_pls_pchem_model
-    algorithms = {
-      :descriptors => {
-        :method => "properties",
-        :categories => ["Proteomics"]
-      },
-      :prediction => {:method => 'Algorithm::Caret.pls' },
-      :feature_selection => {
-        :method => "Algorithm::FeatureSelection.correlation_filter",
-      },
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    assert_equal "Algorithm::Caret.pls", model.algorithms[:prediction][:method]
-    cv = CrossValidation.create model
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-=end
-
-  def test_validate_proteomics_pchem_default_model
-    algorithms = {
-      :descriptors => {
-        :method => "properties",
-        :categories => ["Proteomics","P-CHEM"]
-      },
-      :feature_selection => {
-        :method => "Algorithm::FeatureSelection.correlation_filter",
-      },
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    cv = CrossValidation.create model
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-  def test_nanoparticle_fingerprint_model_without_feature_selection
-    algorithms = {
-      :descriptors => {
-        :method => "fingerprint",
-        :type => "MP2D",
-      },
-      :similarity => {
-        :method => "Algorithm::Similarity.tanimoto",
-        :min => 0.1
-      },
-      :feature_selection => nil
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    cv = CrossValidation.create model
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-  def test_nanoparticle_fingerprint_weighted_average_model_without_feature_selection
-    algorithms = {
-      :descriptors => {
-        :method => "fingerprint",
-        :type => "MP2D",
-      },
-      :similarity => {
-        :method => "Algorithm::Similarity.tanimoto",
-        :min => 0.1
-      },
-      :prediction => { :method => "OpenTox::Algorithm::Regression.weighted_average" },
-      :feature_selection => nil
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    cv = CrossValidation.create model
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-  def test_nanoparticle_fingerprint_model_with_feature_selection
-    algorithms = {
-      :descriptors => {
-        :method => "fingerprint",
-        :type => "MP2D",
-      },
-      :similarity => {
-        :method => "Algorithm::Similarity.tanimoto",
-        :min => 0.1
-      },
-      :feature_selection => {
-        :method => "Algorithm::FeatureSelection.correlation_filter",
-      },
-    }
-    model = Model::Lazar.create prediction_feature: @prediction_feature, training_dataset: @training_dataset, algorithms: algorithms
-    cv = CrossValidation.create model
-    refute_nil cv.r_squared
-    refute_nil cv.rmse
-  end
-
-end