def test_gaussian_symmetries():
rng = ensure_rng(10)
for n in (5, 8, 100, 200):
for sym in rmt.sym_list:
if sym not in ('A', 'D', 'AI') and n % 2:
raises(ValueError, rmt.gaussian, 5, sym)
continue
h = rmt.gaussian(n, sym, rng=rng)
if rmt.t(sym):
t_mat = np.array(rmt.h_t_matrix[sym])
t_mat = np.kron(np.identity(n // len(t_mat)), t_mat)
assert_allclose(h,
np.dot(t_mat, np.dot(h.conj(), t_mat)),
err_msg='TRS broken in ' + sym)
if rmt.p(sym):
p_mat = np.array(rmt.h_p_matrix[sym])
p_mat = np.kron(np.identity(n // len(p_mat)), p_mat)
assert_allclose(h,
-np.dot(p_mat, np.dot(h.conj(), p_mat)),
err_msg='PHS broken in ' + sym)
if rmt.c(sym):
sz = np.kron(np.identity(n // 2), np.diag([1, -1]))
assert_allclose(h,
-np.dot(sz, np.dot(h, sz)),
err_msg='SLS broken in ' + sym)
def test_gaussian_distributions():
np.random.seed(1)
n = 8
for sym in rmt.sym_list:
matrices = np.array([rmt.gaussian(n, sym)[-1, 0] for i in range(3000)])
matrices = matrices.imag if sym in ('D', 'BDI') else matrices.real
ks = stats.kstest(matrices, 'norm')
assert (ks[1] > 0.1), (sym, ks)
def test_gaussian_distributions():
rng = ensure_rng(1)
n = 8
for sym in rmt.sym_list:
matrices = np.array(
[rmt.gaussian(n, sym, rng=rng)[-1, 0] for i in range(3000)])
matrices = matrices.imag if sym in ('D', 'BDI') else matrices.real
ks = stats.kstest(matrices, 'norm')
assert (ks[1] > 0.1), (sym, ks)
def test_gaussian_symmetries():
np.random.seed(10)
for n in (5, 8, 100, 200):
for sym in rmt.sym_list:
if sym not in ('A', 'D', 'AI') and n % 2:
assert_raises(ValueError, rmt.gaussian, 5, sym)
continue
h = rmt.gaussian(n, sym)
if rmt.t(sym):
t_mat = np.array(rmt.h_t_matrix[sym])
t_mat = np.kron(np.identity(n / len(t_mat)), t_mat)
assert_allclose(h, np.dot(t_mat, np.dot(h.conj(), t_mat)),
err_msg='TRS broken in ' + sym)
if rmt.p(sym):
p_mat = np.array(rmt.h_p_matrix[sym])
p_mat = np.kron(np.identity(n / len(p_mat)), p_mat)
assert_allclose(h, -np.dot(p_mat, np.dot(h.conj(), p_mat)),
err_msg='PHS broken in ' + sym)
if rmt.c(sym):
sz = np.kron(np.identity(n / 2), np.diag([1, -1]))
assert_allclose(h, -np.dot(sz, np.dot(h, sz)),
err_msg='SLS broken in ' + sym)