def test_compute_debiasing():
"""Test source amplitude debiasing"""
rng = np.random.RandomState(42)
G = rng.randn(10, 4)
X = rng.randn(4, 20)
debias_true = np.arange(1, 5, dtype=np.float)
M = np.dot(G, X * debias_true[:, np.newaxis])
debias = compute_bias(M, G, X, max_iter=10000, n_orient=1, tol=1e-7)
assert_almost_equal(debias, debias_true, decimal=5)
debias = compute_bias(M, G, X, max_iter=10000, n_orient=2, tol=1e-5)
assert_almost_equal(debias, [1.8, 1.8, 3.72, 3.72], decimal=2)
def test_compute_debiasing():
"""Test source amplitude debiasing"""
rng = np.random.RandomState(42)
G = rng.randn(10, 4)
X = rng.randn(4, 20)
debias_true = np.arange(1, 5, dtype=np.float)
M = np.dot(G, X * debias_true[:, np.newaxis])
debias = compute_bias(M, G, X, max_iter=10000, n_orient=1, tol=1e-7)
assert_almost_equal(debias, debias_true, decimal=5)
debias = compute_bias(M, G, X, max_iter=10000, n_orient=2, tol=1e-5)
assert_almost_equal(debias, [1.8, 1.8, 3.72, 3.72], decimal=2)