def test_negative_scalar_index(adata, index: int, obs: bool):
    pos_index = index + (adata.n_obs if obs else adata.n_vars)

    if obs:
        adata_pos_subset = adata[pos_index]
        adata_neg_subset = adata[index]
    else:
        adata_pos_subset = adata[:, pos_index]
        adata_neg_subset = adata[:, index]

    np.testing.assert_array_equal(
        adata_pos_subset.obs_names, adata_neg_subset.obs_names
    )
    np.testing.assert_array_equal(
        adata_pos_subset.var_names, adata_neg_subset.var_names
    )
def _match_less_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