def test_deepcopy_subset(adata, spmat: type):
    adata.obsp["arr"] = np.zeros((adata.n_obs, adata.n_obs))
    adata.obsp["spmat"] = spmat((adata.n_obs, adata.n_obs))

    adata = deepcopy(adata[:10].copy())

    assert isinstance(adata.obsp["arr"], np.ndarray)
    assert not isinstance(adata.obsp["arr"], ArrayView)
    np.testing.assert_array_equal(adata.obsp["arr"].shape, (10, 10))

    assert isinstance(adata.obsp["spmat"], spmat)
    assert not isinstance(
        adata.obsp["spmat"],
        SparseCSRView if spmat is sparse.csr_matrix else SparseCSCView,
    )
    np.testing.assert_array_equal(adata.obsp["spmat"].shape, (10, 10))
def _match_greater_than(search_base, attribute, value, candidates):
        matches = list()
        for entry in candidates:
            dn = entry.get("dn")
            if not dn.endswith(search_base):
                continue

            value_from_directory = entry.get("attributes").get(attribute)
            if str(value_from_directory) > str(value):
                entry["type"] = "searchResEntry"
                matches.append(entry)

        return matches