def test_view_mixin_copies_data(adata, array_type: type, attr):
    N = 100
    adata = ad.AnnData(
        obs=pd.DataFrame(index=np.arange(N)), var=pd.DataFrame(index=np.arange(N))
    )

    X = array_type(sparse.eye(N, N).multiply(np.arange(1, N + 1)))
    if attr == "X":
        adata.X = X
    else:
        getattr(adata, attr)["arr"] = X

    view = adata[:50]

    if attr == "X":
        arr_view = view.X
    else:
        arr_view = getattr(view, attr)["arr"]

    arr_view_copy = arr_view.copy()

    if sparse.issparse(X):
        assert not np.shares_memory(arr_view.indices, arr_view_copy.indices)
        assert not np.shares_memory(arr_view.indptr, arr_view_copy.indptr)
        assert not np.shares_memory(arr_view.data, arr_view_copy.data)

        arr_view_copy.data[0] = -5
        assert not np.array_equal(arr_view_copy.data, arr_view.data)
    else:
        assert not np.shares_memory(arr_view, arr_view_copy)

        arr_view_copy[0, 0] = -5
        assert not np.array_equal(arr_view_copy, arr_view)
def __init__(self, root, split="train", transforms=None):
        super().__init__(root=root, transforms=transforms)

        verify_str_arg(split, "split", valid_values=("train", "test"))

        root = Path(root) / "KittiFlow" / (split + "ing")
        images1 = sorted(glob(str(root / "image_2" / "*_10.png")))
        images2 = sorted(glob(str(root / "image_2" / "*_11.png")))

        if not images1 or not images2:
            raise FileNotFoundError(
                "Could not find the Kitti flow images. Please make sure the directory structure is correct."
            )

        for img1, img2 in zip(images1, images2):
            self._image_list += [[img1, img2]]

        if split == "train":
            self._flow_list = sorted(glob(str(root / "flow_occ" / "*_10.png")))