void PerformanceFunctionalTest::test_set_default(void) {
  message += "test_set_default\n";

  PerformanceFunctional pf;

  // Test

  pf.set_default();
}
void PerformanceFunctionalTest::test_get_neural_network_pointer(void) {
  message += "test_get_neural_network_pointer\n";

  PerformanceFunctional pf;
  NeuralNetwork nn;

  // Test

  pf.set_neural_network_pointer(&nn);
  assert_true(pf.get_neural_network_pointer() != NULL, LOG);
}
void PerformanceFunctionalTest::test_get_display(void) {
  message += "test_get_display\n";

  PerformanceFunctional pf;

  // Test

  pf.set_display(true);
  assert_true(pf.get_display() == true, LOG);

  pf.set_display(false);
  assert_true(pf.get_display() == false, LOG);
}
void PerformanceFunctionalTest::test_save(void) {
  message += "test_save\n";

  std::string file_name = "../data/performance_functional.xml";

  PerformanceFunctional pf;

  pf.set_objective_type(PerformanceFunctional::MINKOWSKI_ERROR_OBJECTIVE);
  pf.set_regularization_type(
      PerformanceFunctional::NEURAL_PARAMETERS_NORM_REGULARIZATION);

  pf.save(file_name);
}
void PerformanceFunctionalTest::test_to_XML(void)
{
   message += "test_to_XML\n";

   PerformanceFunctional pf;

   pf.set_objective_type(PerformanceFunctional::MINKOWSKI_ERROR_OBJECTIVE);
   pf.set_regularization_type(PerformanceFunctional::NEURAL_PARAMETERS_NORM_REGULARIZATION);

   tinyxml2::XMLDocument* document = pf.to_XML();

   assert_true(document != NULL, LOG);

   delete document;
}