def test_resize_pred(): from pymks import MKSRegressionModel from pymks.bases import DiscreteIndicatorBasis nx, ny = 21, 21 resize = 3 X_delta, y_delta = get_delta_data(nx, ny) X_test, y_test = get_random_data(nx, ny) X_big_test, y_big_test = get_random_data(resize * nx, resize * ny) basis = DiscreteIndicatorBasis(n_states=2) model = MKSRegressionModel(basis) model.fit(X_delta, y_delta) y_pred = model.predict(X_test) assert np.allclose(y_pred, y_test, rtol=1e-2, atol=6.1e-3) model.resize_coeff((resize * nx, resize * ny)) y_big_pred = model.predict(X_big_test) assert np.allclose(y_big_pred, y_big_test, rtol=1e-2, atol=6.1e-2)
def test_MKS_elastic_random(): from pymks import MKSRegressionModel from pymks.bases import DiscreteIndicatorBasis nx, ny = 21, 21 X_delta, y_delta = get_delta_data(nx, ny) X_test, y_test = get_random_data(nx, ny) basis = DiscreteIndicatorBasis(n_states=2) model = MKSRegressionModel(basis) model.fit(X_delta, y_delta) y_pred = model.predict(X_test) assert np.allclose(y_pred, y_test, rtol=1e-2, atol=6.1e-3)