def test_mul_sparse_broadcast(self, mat_s, ket_d):
ca = mul(mat_s, ket_d)
cn = np.multiply(mat_s.A, ket_d)
assert_allclose(ca.A, cn)
ca = mul(mat_s.H, ket_d)
cn = np.multiply(mat_s.H.A, ket_d)
assert_allclose(ca.A, cn)
def test_mul_broadcast(self, mat_d, ket_d):
ca = mul(mat_d, ket_d)
assert isinstance(ca, np.matrix)
cn = np.multiply(mat_d, ket_d)
assert_allclose(ca, cn)
ca = mul(mat_d.H, ket_d)
assert isinstance(ca, np.matrix)
cn = np.multiply(mat_d.H, ket_d)
assert_allclose(ca, cn)
def test_mul_sparse(self, mat_s, mat_s2):
cq = mul(mat_s, mat_s2)
cn = mat_s.A * mat_s2.A
assert issparse(cq)
assert_allclose(cq.A, cn)
cq = mul(mat_s2.A, mat_s)
cn = mat_s2.A * mat_s.A
assert issparse(cq)
assert_allclose(cq.A, cn)
def test_mul_dense_same(self, mat_d, mat_d2):
ca = mul(mat_d, mat_d2)
assert isinstance(ca, np.matrix)
cn = np.multiply(mat_d, mat_d2)
assert_allclose(ca, cn)