def test_weight_scaling():
weights = np.array([[0.1, 0.6, 0.3]])
beta = np.array([[1.0, 2.0, 1.0]])
correct = np.array([[0.3/0.55, 0.15/0.55, 0.1/0.55]])
result = ext_weno.scaled_weights(1, 3, 1e-6, weights, beta)
np.testing.assert_almost_equal(np.sum(result), 1.0)
np.testing.assert_almost_equal(result, correct, 5)
def compute_helper(now, padded, half_width, side_index, coeffs, smoothness, weights, eps):
cells = len(now)
weights = weights[:, side_index]
coeffs = coeffs[:, side_index]
beta = ext_weno.mult_with_smoothness(cells, half_width,
padded, smoothness)
s_weights = ext_weno.scaled_weights(cells, half_width,
eps, weights, beta)
small_polynomials = ext_weno.mult_with_coeffs(cells, half_width,
padded, coeffs)
reconstruction = ext_weno.mult_polynomials(cells, half_width,
s_weights, small_polynomials)
return np.array(reconstruction)
