def test_set_scalar_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(np.zeros((10, 10))))
    orig_X_val = adata.X.copy()
    subset_idx = slice_subset(adata.obs_names)

    adata_subset = adata[subset_idx, :]

    adata_subset.X = 1

    assert adata_subset.is_view
    assert np.all(asarray(adata[subset_idx, :].X) == 1)

    assert asarray((orig_X_val != adata.X)).sum() == mul(*adata_subset.shape)
def _match_greater_than_or_equal(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