Utils

PyALAF.utils.calculate_errors(y_true, mean)[source]

PyALAF.utils.check_model(regression_model, acquisition_function)[source]

PyALAF.utils.fit_model(x, y, regression_model, poly_transformer=None)[source]

PyALAF.utils.generate_pool(dimensions, lim, points=20)[source]

PyALAF.utils.make_prediction(x, regression_model, poly_transformer=None, fictive_noise_level=0)[source]

PyALAF.utils.results_to_df(n_observations, scores_train, max_value, scores_test=None, single_update=False)[source]