validations fixed (all models were executed with default parameters)

1 files changed, 60 insertions, 6 deletions

diff --git a/test/validation.rb b/test/validation.rb
index dfa2c81..9717ccc 100644
--- a/test/validation.rb
+++ b/test/validation.rb
@@ -20,10 +20,25 @@ class ValidationTest < MiniTest::Test
   end
 
   def test_regression_crossvalidation
-    #dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi.csv"
-    dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.csv"
-    model = Model::LazarRegression.create dataset
+    dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.medi.csv"
+    #dataset = Dataset.from_csv_file "#{DATA_DIR}/EPAFHM.csv"
+    params = {
+      :prediction_algorithm => "OpenTox::Algorithm::Regression.weighted_average",
+      :neighbor_algorithm => "fingerprint_neighbors",
+      :neighbor_algorithm_parameters => {
+        :type => "MACCS",
+        :min_sim => 0.7,
+      }
+    }
+    model = Model::LazarRegression.create dataset, params
     cv = RegressionCrossValidation.create model
+    cv.validation_ids.each do |vid|
+      model = Model::Lazar.find(Validation.find(vid).model_id)
+      assert_equal params[:neighbor_algorithm_parameters][:type], model[:neighbor_algorithm_parameters][:type]
+      assert_equal params[:neighbor_algorithm_parameters][:min_sim], model[:neighbor_algorithm_parameters][:min_sim]
+      refute_equal params[:neighbor_algorithm_parameters][:training_dataset_id], model[:neighbor_algorithm_parameters][:training_dataset_id]
+    end
+
     #`inkview #{cv.plot}`
     #puts JSON.pretty_generate(cv.misclassifications)#.collect{|l| l.join ", "}.join "\n"
     #`inkview #{cv.plot}`
@@ -37,12 +52,51 @@ class ValidationTest < MiniTest::Test
     dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv"
     model = Model::LazarClassification.create dataset
     repeated_cv = RepeatedCrossValidation.create model
-    p repeated_cv
     repeated_cv.crossvalidations.each do |cv|
-      p cv
-      p cv.accuracy
       assert cv.accuracy > 0.7
     end
   end
 
+  def test_crossvalidation_parameters
+    dataset = Dataset.from_csv_file "#{DATA_DIR}/hamster_carcinogenicity.csv"
+    params = {
+      :neighbor_algorithm_parameters => {
+        :min_sim => 0.3,
+        :type => "FP3"
+      }
+    }
+    model = Model::LazarClassification.create dataset, params
+    model.save
+    cv = ClassificationCrossValidation.create model
+    params = model.neighbor_algorithm_parameters
+    params = Hash[params.map{ |k, v| [k.to_s, v] }] # convert symbols to string
+    cv.validations.each do |validation|
+      assert_equal params, validation.model.neighbor_algorithm_parameters
+    end
+  end
+
+  def test_physchem_regression_crossvalidation
+
+    @descriptors = OpenTox::Algorithm::Descriptor::OBDESCRIPTORS.keys
+    refute_empty @descriptors
+
+    # UPLOAD DATA
+    training_dataset = OpenTox::Dataset.from_csv_file File.join(DATA_DIR,"EPAFHM.medi.csv")
+    feature_dataset = Algorithm::Descriptor.physchem training_dataset, @descriptors
+    feature_dataset.save
+    scaled_feature_dataset = feature_dataset.scale
+    scaled_feature_dataset.save
+    model = Model::LazarRegression.create training_dataset
+    model.neighbor_algorithm = "physchem_neighbors"
+    model.neighbor_algorithm_parameters = {
+      :feature_calculation_algorithm => "OpenTox::Algorithm::Descriptor.physchem",
+      :descriptors => @descriptors,
+      :feature_dataset_id => scaled_feature_dataset.id,
+      :min_sim => 0.3
+    }
+    model.save
+    cv = RegressionCrossValidation.create model
+    p cv
+  end
+
 end