def test_hafnian_batched():
"""Test hafnian_batched against hafnian_repeated for a random symmetric matrix"""
n_modes = 4
A = np.random.rand(n_modes, n_modes) + 1j * np.random.rand(n_modes, n_modes)
A += A.T
n_photon = 5
v1 = np.array([hafnian_repeated(A, q) for q in product(np.arange(n_photon), repeat=n_modes)])
assert np.allclose(hafnian_batched(A, n_photon, make_tensor=False), v1)
def test_hafnian_batched_zero_loops_no_edges():
"""Test hafnian_batched with loops against hafnian_repeated with loops for a the zero matrix
and a loops
"""
n_modes = 4
A = np.zeros([n_modes, n_modes], dtype=complex)
n_photon = 5
v1 = np.array(
[hafnian_repeated(A, q, loop=True) for q in product(np.arange(n_photon), repeat=n_modes)]
)
expected = hafnian_batched(A, n_photon, make_tensor=False)
assert np.allclose(expected, v1)
def test_hafnian_batched_loops_no_edges():
"""Test hafnian_batched with loops against hafnian_repeated with loops for a random symmetric matrix
and a random vector of loops
"""
n_modes = 4
A = np.zeros([n_modes, n_modes], dtype=complex)
mu = np.random.rand(n_modes) + 1j * np.random.rand(n_modes)
n_photon = 5
v1 = np.array([
hafnian_repeated(A, q, mu=mu, loop=True)
for q in product(np.arange(n_photon), repeat=n_modes)
])
expected = hafnian_batched(A, n_photon, mu=mu, make_tensor=False)
assert np.allclose(expected, v1)