def test_mpo_zeros_like(self):
A = MPO_rand(10, 7, phys_dim=3, normalize=False)
Z = MPO_zeros_like(A)
assert A @ Z == 0.0
x1 = A.trace()
x2 = (A + Z).trace()
assert_allclose(x1, x2)
def test_mpo_zeros_like(self, cyclic):
A = MPO_rand(10, 7, phys_dim=3, normalize=False, cyclic=cyclic)
Z = MPO_zeros_like(A)
assert A @ Z == 0.0
assert Z.cyclic == cyclic
x1 = A.trace()
x2 = (A + Z).trace()
assert_allclose(x1, x2)
def test_apply_mps(self, cyclic, site_ind_id):
A = MPO_rand(8, 5, cyclic=cyclic)
x = MPS_rand_state(8, 4, site_ind_id=site_ind_id, cyclic=cyclic)
y = A.apply(x)
assert y.max_bond() == 20
assert isinstance(y, MatrixProductState)
assert len(y.tensors) == 8
assert y.site_ind_id == site_ind_id
def test_compress_mpo(self, cyclic):
A = MPO_rand(12, 5, cyclic=cyclic)
assert all(b == 5 for b in A.bond_sizes())
A.expand_bond_dimension(10)
assert all(b == 10 for b in A.bond_sizes())
A.compress()
assert all(b in (4, 5) for b in A.bond_sizes())
def test_dot_mpo(self):
A, B = MPO_rand(8, 5), MPO_rand(8,
5,
upper_ind_id='q{}',
lower_ind_id='w{}')
C = A.apply(B)
assert C.max_bond() == 25
assert C.upper_ind_id == 'q{}'
assert C.lower_ind_id == 'w{}'
Ad, Bd, Cd = A.to_dense(), B.to_dense(), C.to_dense()
assert_allclose(Ad @ Bd, Cd)
def test_apply_mpo(self, cyclic):
A = MPO_rand(8, 5, cyclic=cyclic)
B = MPO_rand(8,
5,
upper_ind_id='q{}',
lower_ind_id='w{}',
cyclic=cyclic)
C = A.apply(B)
assert C.max_bond() == 25
assert C.upper_ind_id == 'q{}'
assert C.lower_ind_id == 'w{}'
Ad, Bd, Cd = A.to_dense(), B.to_dense(), C.to_dense()
assert_allclose(Ad @ Bd, Cd)
def test_subtract_mpo(self, cyclic):
a, b = MPO_rand(13, 7, cyclic=cyclic), MPO_rand(13, 7, cyclic=cyclic)
x1 = a.trace() - b.trace()
assert_allclose(x1, (a - b).trace())
a -= b
assert_allclose(x1, a.trace())
def test_upper_lower_ind_id_guard(self):
A = MPO_rand(8, 5)
with pytest.raises(ValueError):
A.upper_ind_id = 'b{}'
with pytest.raises(ValueError):
A.lower_ind_id = 'k{}'