validation statistic fixes

1 files changed, 0 insertions, 54 deletions

diff --git a/test/nanomaterial-model-validation.rb b/test/nanomaterial-model-validation.rb
deleted file mode 100644
index 9eaa17d..0000000
--- a/test/nanomaterial-model-validation.rb
+++ /dev/null
@@ -1,54 +0,0 @@
-require_relative "setup.rb"
-
-class NanomaterialValidationModelTest < MiniTest::Test
-
-  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_default_nanomaterial_validation_model
-    validation_model = Model::Validation.from_enanomapper
-    [:endpoint,:species,:source].each do |p|
-      refute_empty validation_model[p]
-    end
-    assert validation_model.regression?
-    refute validation_model.classification?
-    validation_model.crossvalidations.each do |cv|
-      refute_nil cv.r_squared
-      refute_nil cv.rmse
-    end
-    nanoparticle = @training_dataset.nanoparticles[-34]
-    assert_includes nanoparticle.dataset_ids, @training_dataset.id
-    prediction = validation_model.predict nanoparticle
-    refute_nil prediction[:value]
-    assert_includes prediction[:prediction_interval][0]..prediction[:prediction_interval][1], prediction[:measurements].median, "This assertion assures that measured values are within the prediction interval. It may fail in 5% of the predictions."
-    validation_model.delete
-  end
-
-  def test_nanomaterial_validation_model_parameters
-    algorithms = {
-      :descriptors => {
-        :method => "fingerprint",
-        :type => "MP2D",
-      },
-      :similarity => {
-        :method => "Algorithm::Similarity.tanimoto",
-        :min => 0.1
-      },
-      :prediction => { :method => "OpenTox::Algorithm::Regression.weighted_average" },
-      :feature_selection => nil
-    }
-    validation_model = Model::Validation.from_enanomapper algorithms: algorithms
-    assert validation_model.regression?
-    refute validation_model.classification?
-    validation_model.crossvalidations.each do |cv|
-      refute_nil cv.r_squared
-      refute_nil cv.rmse
-    end
-    nanoparticle = @training_dataset.nanoparticles[-34]
-    assert_includes nanoparticle.dataset_ids, @training_dataset.id
-    prediction = validation_model.predict nanoparticle
-    refute_nil prediction[:value]
-  end
-end