def test_matrix_inv():
A = D.array([
[-1.0, 3 / 2],
[1.0, -1.0],
], dtype=D.float64)
Ainv = D.matrix_inv(A)
assert (D.max(D.abs(D.to_float(Ainv @ A - D.eye(2)))) <= 8 * D.epsilon())
def test_matrix_inv_bigger():
for diag_size in range(2, 101):
np.random.seed(15)
for trial in range(3):
A = np.random.normal(size=(diag_size, diag_size))
while np.abs(np.linalg.det(D.to_float(A))) <= 1e-5:
A = np.random.normal(size=(diag_size, diag_size), std=250.0)
A = D.array(D.cast_to_float_fmt(A))
Ainv = D.matrix_inv(A)
assert (
D.max(D.abs(D.to_float(Ainv @ A - D.eye(diag_size)))) <=
4 * D.epsilon()**0.5
), "Matrix inversion failed for diagonal with size: " + str(
diag_size)
def do(self, A):
Ainv = D.matrix_inv(A)
assert (D.max(D.abs(D.to_float(Ainv @ A - D.eye(A.shape[0])))) <=
256 * D.epsilon())
def do(self, A):
with pytest.raises(np.linalg.LinAlgError):
D.matrix_inv(D.zeros((2, 3)))
with pytest.raises(np.linalg.LinAlgError):
D.matrix_inv(D.zeros((5, 2, 3)))
def test_matrix_inv_exceptions():
with pytest.raises(np.linalg.LinAlgError):
D.matrix_inv(D.zeros((2, 3), dtype=D.float64))
with pytest.raises(np.linalg.LinAlgError):
D.matrix_inv(D.zeros((5, 2, 3), dtype=D.float64))