def test_set_varm(adata):
    init_hash = joblib.hash(adata)

    dim0_size = np.random.randint(2, adata.shape[1] - 1)
    dim1_size = np.random.randint(1, 99)
    orig_varm_val = adata.varm["o"].copy()
    subset_idx = np.random.choice(adata.var_names, dim0_size, replace=False)

    subset = adata[:, subset_idx]
    assert subset.is_view
    subset.varm = dict(o=np.ones((dim0_size, dim1_size)))
    assert not subset.is_view
    assert np.all(orig_varm_val == adata.varm["o"])  # Checking for mutation
    assert np.all(subset.varm["o"] == np.ones((dim0_size, dim1_size)))

    subset = adata[:, subset_idx]
    subset_hash = joblib.hash(subset)
    with pytest.raises(ValueError):
        subset.varm = dict(o=np.ones((dim0_size + 1, dim1_size)))
    with pytest.raises(ValueError):
        subset.varm = dict(o=np.ones((dim0_size - 1, dim1_size)))
    # subset should not be changed by failed setting
    assert subset_hash == joblib.hash(subset)
    assert init_hash == joblib.hash(adata)
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