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

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

    new_obs = pd.DataFrame(
        dict(a=np.ones(subset.n_obs), b=np.ones(subset.n_obs)),
        index=subset.obs_names,
    )

    assert subset.is_view
    subset.obs = new_obs
    assert not subset.is_view
    assert np.all(subset.obs == new_obs)

    assert joblib.hash(adata) == init_hash
def _read_16bits_png_with_flow_and_valid_mask(file_name):

    flow_and_valid = _read_png_16(file_name).to(torch.float32)
    flow, valid_flow_mask = flow_and_valid[:2, :, :], flow_and_valid[2, :, :]
    flow = (flow - 2 ** 15) / 64  # This conversion is explained somewhere on the kitti archive
    valid_flow_mask = valid_flow_mask.bool()

    # For consistency with other datasets, we convert to numpy
    return flow.numpy(), valid_flow_mask.numpy()