def test_ndarrays(self):
a = rand_matrix(2)
i = eye(2)
b = eyepad([a], np.array([2, 2, 2]), [0, 2])
assert_allclose(b, a & i & a)
b = eyepad([a], [2, 2, 2], np.array([0, 2]))
assert_allclose(b, a & i & a)
def test_sparse(self):
i = eye(2, sparse=True)
a = qu(rand_matrix(2), sparse=True)
b = eyepad(a, [2, 2, 2], 1) # infer sparse
assert(issparse(b))
assert_allclose(b.A, (i & a & i).A)
a = rand_matrix(2)
b = eyepad(a, [2, 2, 2], 1, sparse=True) # explicit sparse
assert(issparse(b))
assert_allclose(b.A, (i & a & i).A)
def test_overlap(self):
a = [rand_matrix(4) for i in range(2)]
dims1 = [2, 2, 2, 2, 2, 2]
dims2 = [2, 4, 4, 2]
b = eyepad(a, dims1, [1, 2, 3, 4])
c = eyepad(a, dims2, [1, 2])
assert_allclose(c, b)
dims2 = [4, 2, 2, 4]
b = eyepad(a, dims1, [0, 1, 4, 5])
c = eyepad(a, dims2, [0, 3])
assert_allclose(c, b)
def test_basic(self):
a = rand_matrix(2)
i = eye(2)
dims = [2, 2, 2]
b = eyepad([a], dims, [0])
assert_allclose(b, a & i & i)
b = eyepad([a], dims, [1])
assert_allclose(b, i & a & i)
b = eyepad([a], dims, [2])
assert_allclose(b, i & i & a)
b = eyepad([a], dims, [0, 2])
assert_allclose(b, a & i & a)
b = eyepad([a], dims, [0, 1, 2])
assert_allclose(b, a & a & a)
def test_2d_simple(self):
a = (rand_matrix(2), rand_matrix(2))
dims = ((2, 3), (3, 2))
inds = ((0, 0), (1, 1))
b = eyepad(a, dims, inds)
assert b.shape == (36, 36)
assert_allclose(b, a[0] & eye(9) & a[1])
def test_mid_multi_reverse(self):
a = [rand_matrix(2) for i in range(3)]
i = eye(2)
dims = [2, 2, 2, 2, 2, 2]
inds = [5, 4, 1]
b = eyepad(a, dims, inds)
assert_allclose(b, i & a[2] & i & i & a[1] & a[0])
def test_graph_state_1d(self):
n = 5
p = graph_state_1d(n, cyclic=True)
for j in range(n):
k = eyepad(
[pauli('x'), pauli('z'), pauli('z')], [2] * n,
(j, (j - 1) % n, (j + 1) % n))
o = p.H @ k @ p
np.testing.assert_allclose(o, 1)
def test_quevo_at_times(self):
ham = ham_heis(2, cyclic=False)
p0 = up() & down()
sim = QuEvo(p0, ham, method='solve')
ts = np.linspace(0, 10)
for t, pt in zip(ts, sim.at_times(ts)):
x = cos(t)
y = expec(pt, eyepad(pauli('z'), [2, 2], 0))
assert_allclose(x, y, atol=1e-15)
def test_sparse_format_outputs_with_dense(self, od1, stype, pos,
coo_build):
x = eyepad(od1, [3, 3, 3], pos, sparse=True,
stype=stype, coo_build=coo_build)
try:
default = "bsr" if (2 in pos and not coo_build) else "csr"
except TypeError:
default = "bsr" if (pos == 2 and not coo_build) else "csr"
assert x.format == default if stype is None else stype
def test_holey_overlap(self):
a = rand_matrix(8)
dims1 = (2, 2, 2, 2, 2)
dims2 = (2, 8, 2)
b = eyepad(a, dims1, (1, 3))
c = eyepad(a, dims2, 1)
assert_allclose(b, c)
dims1 = (2, 2, 2, 2, 2)
dims2 = (2, 2, 8)
b = eyepad(a, dims1, (2, 4))
c = eyepad(a, dims2, 2)
assert_allclose(b, c)
dims1 = (2, 2, 2, 2, 2)
dims2 = (8, 2, 2)
b = eyepad(a, dims1, (0, 2))
c = eyepad(a, dims2, 0)
assert_allclose(b, c)
def test_sparse_format_outputs(self, os1, stype, pos, coo_build):
x = eyepad(os1, [3, 3, 3], pos,
stype=stype, coo_build=coo_build)
assert x.format == "csr" if stype is None else stype
def test_auto(self):
a = rand_matrix(2)
i = eye(2)
b = eyepad([a], (2, -1, 2), [1])
assert_allclose(b, i & a & i)