def test_view_of_view_modification():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata[0, :][:, 5:].X = np.ones(5)
    assert np.all(adata.X[0, 5:] == np.ones(5))
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2))
    assert np.all(adata.X[1:3, 1:3] == np.ones((2, 2)))

    adata.X = sparse.csr_matrix(adata.X)
    adata[0, :][:, 5:].X = np.ones(5) * 2
    assert np.all(asarray(adata.X)[0, 5:] == np.ones(5) * 2)
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2)) * 2
    assert np.all(asarray(adata.X)[1:3, 1:3] == np.ones((2, 2)) * 2)
def __init__(self, root, split="train", pass_name="clean", transforms=None):
        super().__init__(root=root, transforms=transforms)

        verify_str_arg(split, "split", valid_values=("train", "test"))
        verify_str_arg(pass_name, "pass_name", valid_values=("clean", "final", "both"))
        passes = ["clean", "final"] if pass_name == "both" else [pass_name]

        root = Path(root) / "Sintel"
        flow_root = root / "training" / "flow"

        for pass_name in passes:
            split_dir = "training" if split == "train" else split
            image_root = root / split_dir / pass_name
            for scene in os.listdir(image_root):
                image_list = sorted(glob(str(image_root / scene / "*.png")))
                for i in range(len(image_list) - 1):
                    self._image_list += [[image_list[i], image_list[i + 1]]]

                if split == "train":
                    self._flow_list += sorted(glob(str(flow_root / scene / "*.flo")))