def test_almost_equal(vector_arrays, tolerances, norms):
v1, v2 = vector_arrays
rtol, atol = tolerances
n, o = norms
try:
dv1 = v1.to_numpy()
dv2 = v2.to_numpy()
except NotImplementedError:
dv1 = dv2 = None
for ind1, ind2 in valid_inds_of_same_length(v1, v2):
try:
r = almost_equal(v1[ind1], v2[ind2], norm=n, rtol=rtol, atol=atol)
except NotImplementedError as e:
if n == 'l1':
pytest.xfail('l1_norm not implemented')
else:
raise e
assert isinstance(r, np.ndarray)
assert r.shape == (v1.len_ind(ind1), )
if dv1 is not None:
if dv2.shape[1] == 0:
continue
assert np.all(r == (
np.linalg.norm(
indexed(dv1, ind1) -
indexed(dv2, ind2), ord=o, axis=1) <= atol +
rtol * np.linalg.norm(indexed(dv2, ind2), ord=o, axis=1)))
def test_pairwise_apply2(operator_with_arrays):
op, mu, U, V = operator_with_arrays
for U_ind, V_ind in valid_inds_of_same_length(U, V):
M = op.pairwise_apply2(V[V_ind], U[U_ind], mu=mu)
assert M.shape == (V.len_ind(V_ind), )
M2 = V[V_ind].pairwise_inner(op.apply(U[U_ind], mu=mu))
assert np.allclose(M, M2)
def test_almost_equal_incompatible(vector_arrays):
v1, v2 = vector_arrays
for ind1, ind2 in valid_inds_of_same_length(v1, v2):
for n in ['sup', 'l1', 'l2']:
c1, c2 = v1.copy(), v2.copy()
with pytest.raises(Exception):
almost_equal(c1[ind1], c2[ind2], norm=n)
def test_almost_equal(vector_arrays, tolerances, sup_norm):
v1, v2 = vector_arrays
rtol, atol = tolerances
try:
dv1 = v1.to_numpy()
dv2 = v2.to_numpy()
except NotImplementedError:
dv1 = dv2 = None
for ind1, ind2 in valid_inds_of_same_length(v1, v2):
r = almost_equal(v1[ind1],
v2[ind2],
sup_norm=sup_norm,
rtol=rtol,
atol=atol)
assert isinstance(r, np.ndarray)
assert r.shape == (v1.len_ind(ind1), )
if dv1 is not None:
if dv2.shape[1] == 0:
continue
assert np.all(
r == (np.linalg.norm(indexed(dv1, ind1) - indexed(dv2, ind2),
ord=np.inf if sup_norm else None,
axis=1) <= atol +
rtol * np.linalg.norm(indexed(dv2, ind2),
ord=np.inf if sup_norm else None,
axis=1)))
def test_almost_equal_incompatible(vector_arrays):
v1, v2 = vector_arrays
for ind1, ind2 in valid_inds_of_same_length(v1, v2):
for sup_norm in (False, True):
c1, c2 = v1.copy(), v2.copy()
with pytest.raises(Exception):
almost_equal(c1[ind1], c2[ind2], sup_norm=sup_norm)
def test_pairwise_inner_incompatible(vector_arrays):
v1, v2 = vector_arrays
for ind1, ind2 in pyst.valid_inds_of_same_length(v1,
v2,
random_module=False):
c1, c2 = v1.copy(), v2.copy()
with pytest.raises(Exception):
c1[ind1].pairwise_inner(c2[ind2])
def test_axpy_wrong_coefficients(vector_arrays, random):
v1, v2 = vector_arrays
# TODO data input from hypothesis strategy
for ind1, ind2 in pyst.valid_inds_of_same_length(v1, v2):
for alpha in ([
np.array([]),
np.eye(v1.len_ind(ind1)),
np.random.random(v1.len_ind(ind1) + 1)
] if v1.len_ind(ind1) > 0 else [np.random.random(1)]):
with pytest.raises(Exception):
v1[ind1].axpy(alpha, v2[ind2])
def test_axpy(vector_arrays, random):
v1, v2 = vector_arrays
for ind1, ind2 in pyst.valid_inds_of_same_length(v1,
v2,
random_module=False):
if v1.len_ind(ind1) != v1.len_ind_unique(ind1):
with pytest.raises(Exception):
c1, c2 = v1.copy(), v2.copy()
c1[ind1].axpy(0., c2[ind2])
continue
ind1_complement = ind_complement(v1, ind1)
c1, c2 = v1.copy(), v2.copy()
c1[ind1].axpy(0., c2[ind2])
assert len(c1) == len(v1)
assert np.all(almost_equal(c1, v1))
assert np.all(almost_equal(c2, v2))
for a in (1., 1.4, np.random.random(v1.len_ind(ind1))):
c1, c2 = v1.copy(), v2.copy()
c1[ind1].axpy(a, c2[ind2])
assert len(c1) == len(v1)
assert np.all(
almost_equal(c1[ind1_complement], v1[ind1_complement]))
assert np.all(almost_equal(c2, v2))
assert np.all(c1[ind1].sup_norm() <= v1[ind1].sup_norm() +
abs(a) * v2[ind2].sup_norm() * (1. + 1e-10))
assert np.all(c1[ind1].norm() <=
(v1[ind1].norm() + abs(a) * v2[ind2].norm()) *
(1. + 1e-10))
try:
x = v1.to_numpy(True).astype(
complex) # ensure that inplace addition works
if isinstance(ind1, Number):
x[[ind1]] += indexed(v2.to_numpy(), ind2) * a
else:
if isinstance(a, np.ndarray):
aa = a[:, np.newaxis]
else:
aa = a
x[ind1] += indexed(v2.to_numpy(), ind2) * aa
assert np.allclose(c1.to_numpy(), x)
except NotImplementedError:
pass
c1[ind1].axpy(-a, c2[ind2])
assert len(c1) == len(v1)
assert np.all(almost_equal(c1, v1))
def test_almost_equal_product(operator_with_arrays_and_products):
_, _, v1, _, product, _ = operator_with_arrays_and_products
if len(v1) < 2:
return
v2 = v1.empty()
v2.append(v1[:len(v1) // 2])
for ind1, ind2 in valid_inds_of_same_length(v1, v2):
for rtol, atol in ((1e-5, 1e-8), (1e-10, 1e-12), (0., 1e-8), (1e-5,
1e-8)):
r = almost_equal(v1[ind1], v2[ind2], product=product)
assert isinstance(r, np.ndarray)
assert r.shape == (v1.len_ind(ind1), )
assert np.all(
r == ((v1[ind1] - v2[ind2]).norm(product) <= atol + rtol *
(v2[ind2]).norm(product)))
def test_pairwise_inner(vector_arrays):
v1, v2 = vector_arrays
for ind1, ind2 in pyst.valid_inds_of_same_length(v1, v2):
r = v1[ind1].pairwise_inner(v2[ind2])
assert isinstance(r, np.ndarray)
assert r.shape == (v1.len_ind(ind1), )
r2 = v2[ind2].pairwise_inner(v1[ind1])
assert np.allclose, (r, r2)
assert np.all(r <= v1[ind1].norm() * v2[ind2].norm() * (1. + 1e-10))
try:
assert np.allclose(
r,
np.sum(indexed(v1.to_numpy(), ind1).conj() *
indexed(v2.to_numpy(), ind2),
axis=1))
except NotImplementedError:
pass
def test_axpy_incompatible(vector_arrays):
v1, v2 = vector_arrays
for ind1, ind2 in pyst.valid_inds_of_same_length(v1,
v2,
random_module=False):
c1, c2 = v1.copy(), v2.copy()
with pytest.raises(Exception):
c1[ind1].axpy(0., c2[ind2])
c1, c2 = v1.copy(), v2.copy()
with pytest.raises(Exception):
c1[ind1].axpy(1., c2[ind2])
c1, c2 = v1.copy(), v2.copy()
with pytest.raises(Exception):
c1[ind1].axpy(-1., c2[ind2])
c1, c2 = v1.copy(), v2.copy()
with pytest.raises(Exception):
c1[ind1].axpy(1.42, c2[ind2])
