def test_boolean_op(matrix_type, another_matrix_type, boolean_op,
alternate_form):
if boolean_op in SCIPYSPARSE_NOT_IMPLEMENTED and alternate_form == asspmatrix:
pytest.skip("Not supported")
sarr1 = assparsearray(matrix_type(ss.random(100, 100, dtype=bool)))
sarr2 = assparsearray(another_matrix_type(ss.random(100, 100, dtype=bool)))
alt1, alt2 = alternate_form(sarr1), alternate_form(sarr2)
sarr_res = boolean_op(sarr1, sarr2)
alt_res = boolean_op(alt1, alt2)
assert not np.any(sarr_res != alt_res)
def test_indexing(matrix_type, idx):
a = assparsearray(
matrix_type(sparse.random(50, 100, format="csr", density=0.4)))
true_result = a.value.toarray()[idx]
curr_result = a[idx]
np.testing.assert_array_equal(asnparray(curr_result), true_result)
def test_equality():
mtx = ss.random(100, 100, format="csr")
arr = assparsearray(mtx)
assert np.all(arr == arr.copy()) is np.bool_(True)
# assert np.all(mtx == arr) # TODO
assert np.all(arr == mtx)
def test_matmul(matrix_type, another_matrix_type):
mtx1 = matrix_type(ss.random(100, 100))
mtx2 = another_matrix_type(ss.random(100, 100))
arr1, arr2 = assparsearray(mtx1), assparsearray(mtx2)
assert np.all(arr1 @ arr2 == mtx1 @ mtx2)
def test_divide_scalar(matrix_type):
mtx = matrix_type(ss.random(100, 100))
arr = assparsearray(mtx)
assert np.all(arr / 2 == mtx / 2)
def test_subtract(matrix_type, another_matrix_type):
mtx1 = matrix_type(ss.random(100, 100))
mtx2 = another_matrix_type(ss.random(100, 100))
arr1, arr2 = assparsearray(mtx1), assparsearray(mtx2)
assert np.all(arr1 - arr2 == mtx1 - mtx2)
def test_any(matrix_type):
assert not np.any(assparsearray(matrix_type(np.zeros((100, 100)))))
assert np.any(assparsearray(matrix_type(np.eye(100))))
def test_all(matrix_type):
mtx = matrix_type(np.eye(100))
arr = assparsearray(mtx)
assert not np.all(arr)
assert np.all(assparsearray(matrix_type(np.ones((10, 10))))) is npTrue