def test_matmul(a_shape, b_shape, a_format, b_format, a_comp_axes,
b_comp_axes):
if a_format == "coo" or len(a_shape) == 1:
a_comp_axes = None
if b_format == "coo" or len(b_shape) == 1:
b_comp_axes = None
sa = sparse.random(a_shape,
density=0.5,
format=a_format,
compressed_axes=a_comp_axes)
sb = sparse.random(b_shape,
density=0.5,
format=b_format,
compressed_axes=b_comp_axes)
a = sa.todense()
b = sb.todense()
assert_eq(np.matmul(a, b), sparse.matmul(sa, sb))
assert_eq(sparse.matmul(sa, b), sparse.matmul(a, sb))
assert_eq(np.matmul(a, b), sparse.matmul(sa, sb))
if a.ndim == 2 or b.ndim == 2:
assert_eq(
np.matmul(a, b),
sparse.matmul(
scipy.sparse.coo_matrix(a) if a.ndim == 2 else sa,
scipy.sparse.coo_matrix(b) if b.ndim == 2 else sb,
),
)
if hasattr(operator, "matmul"):
assert_eq(operator.matmul(a, b), operator.matmul(sa, sb))
def test_matmul(a_shape, b_shape, a_format, b_format, a_kwargs, b_kwargs):
if len(a_shape) == 1:
a_kwargs = {}
if len(b_shape) == 1:
b_kwargs = {}
sa = sparse.random(a_shape, density=0.5, format=a_format, **a_kwargs)
sb = sparse.random(b_shape, density=0.5, format=b_format, **b_kwargs)
a = sa.todense()
b = sb.todense()
assert_eq(np.matmul(a, b), sparse.matmul(sa, sb))
assert_eq(sparse.matmul(sa, b), sparse.matmul(a, sb))
assert_eq(np.matmul(a, b), sparse.matmul(sa, sb))
if a.ndim == 2 or b.ndim == 2:
assert_eq(
np.matmul(a, b),
sparse.matmul(
scipy.sparse.coo_matrix(a) if a.ndim == 2 else sa,
scipy.sparse.coo_matrix(b) if b.ndim == 2 else sb,
),
)
if hasattr(operator, "matmul"):
assert_eq(operator.matmul(a, b), operator.matmul(sa, sb))
def test_matmul_errors():
with pytest.raises(ValueError):
sa = sparse.random((3, 4, 5, 6), 0.5)
sb = sparse.random((3, 6, 5, 6), 0.5)
sparse.matmul(sa, sb)