def test_set_var(adata, subset_func):
    init_hash = joblib.hash(adata)

    subset = adata[:, subset_func(adata.var_names)]

    new_var = pd.DataFrame(
        dict(a=np.ones(subset.n_vars), b=np.ones(subset.n_vars)),
        index=subset.var_names,
    )

    assert subset.is_view
    subset.var = new_var
    assert not subset.is_view
    assert np.all(subset.var == new_var)

    assert joblib.hash(adata) == init_hash
def normalize(patterns, default, root, cwd, auditor, warn):
            kp = _donormalize(patterns, default, root, cwd, auditor, warn)
            kindpats = []
            for kind, pats, source in kp:
                if kind not in ("re", "relre"):  # regex can't be normalized
                    p = pats
                    pats = dsnormalize(pats)

                    # Preserve the original to handle a case only rename.
                    if p != pats and p in dirstate:
                        kindpats.append((kind, p, source))

                kindpats.append((kind, pats, source))
            return kindpats