def test_resize_coeff():
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_big_delta, y_big_delta = get_delta_data(resize * nx, resize * ny)
basis = DiscreteIndicatorBasis(n_states=2)
model = MKSRegressionModel(basis)
big_model = MKSRegressionModel(basis)
model.fit(X_delta, y_delta)
big_model.fit(X_big_delta, y_big_delta)
model.resize_coeff((resize * nx, resize * ny))
assert np.allclose(model.coef_, big_model.coef_, rtol=1e-2, atol=2.1e-3)
def test_resize_coeff():
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_big_delta, y_big_delta = get_delta_data(resize * nx, resize * ny)
basis = DiscreteIndicatorBasis(n_states=2)
model = MKSRegressionModel(basis)
big_model = MKSRegressionModel(basis)
model.fit(X_delta, y_delta)
big_model.fit(X_big_delta, y_big_delta)
model.resize_coeff((resize * nx, resize * ny))
assert np.allclose(model.coef_, big_model.coef_,
rtol=1e-2, atol=2.1e-3)
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_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)
