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;
}