def test_views():
    X = np.array(X_list)
    adata = ad.AnnData(X, obs=obs_dict, var=var_dict, uns=uns_dict, dtype="int32")

    assert adata[:, 0].is_view
    assert adata[:, 0].X.tolist() == np.reshape([1, 4, 7], (3, 1)).tolist()

    adata[:2, 0].X = [0, 0]

    assert adata[:, 0].X.tolist() == np.reshape([0, 0, 7], (3, 1)).tolist()

    adata_subset = adata[:2, [0, 1]]

    assert adata_subset.is_view
    # now transition to actual object
    adata_subset.obs["foo"] = range(2)
    assert not adata_subset.is_view

    assert adata_subset.obs["foo"].tolist() == list(range(2))
def test_make_gym_venv_nostack(name, num_envs, state_shape, reward_scale):
    seed = 0
    frame_op = None
    frame_op_len = None
    venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
    venv.reset()
    for i in range(5):
        state, reward, done, info = venv.step([venv.action_space.sample()] * num_envs)

    assert isinstance(state, np.ndarray)
    assert state.shape == (num_envs,) + state_shape
    assert isinstance(reward, np.ndarray)
    assert reward.shape == (num_envs,)
    assert isinstance(done, np.ndarray)
    assert done.shape == (num_envs,)
    assert len(info) == num_envs
    venv.close()