def test_save_load_exdir(self): self.data = Data(logger_level="error", backend="exdir") self.setup_mock_data(self.data) folder = os.path.dirname(os.path.realpath(__file__)) compare_file = os.path.join(folder, "data/test_save_mock") filename = os.path.join(self.output_test_dir, "test_save_mock") self.data.save(filename) new_data = Data(filename, backend="exdir") for statistical_metric in self.statistical_metrics: new_data["feature1d"][statistical_metric] = np.array([1., 2.]) new_data["TestingModel1d"][statistical_metric] = np.array([3., 4.]) new_data["feature1d"]["labels"] = ["xlabel", "ylabel"] new_data["TestingModel1d"]["labels"] = ["xlabel", "ylabel"] new_data.model_name = "TestingModel1d" new_data.uncertain_parameters = ["a", "b"] new_data.method = "mock" new_data.seed = 10 new_data.incomplete = ["a", "b"] new_data.error = ["feature1d"]
def create_PCE_custom(self, uncertain_parameters=None): data = Data() q0, q1 = cp.variable(2) parameter_space = [cp.Uniform(), cp.Uniform()] distribution = cp.J(*parameter_space) data.uncertain_parameters = ["a", "b"] data.test_value = "custom PCE method" data.add_features( ["TestingModel1d", "feature0d", "feature1d", "feature2d"]) U_hat = {} U_hat["TestingModel1d"] = cp.Poly([q0, q1 * q0, q1]) U_hat["feature0d"] = cp.Poly([q0, q1 * q0, q1]) U_hat["feature1d"] = cp.Poly([q0, q1 * q0, q1]) U_hat["feature2d"] = cp.Poly([q0, q1 * q0, q1]) return U_hat, distribution, data