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", transforms=None):
        super().__init__(root=root, transforms=transforms)

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

        root = Path(root) / "FlyingChairs"
        images = sorted(glob(str(root / "data" / "*.ppm")))
        flows = sorted(glob(str(root / "data" / "*.flo")))

        split_file_name = "FlyingChairs_train_val.txt"

        if not os.path.exists(root / split_file_name):
            raise FileNotFoundError(
                "The FlyingChairs_train_val.txt file was not found - please download it from the dataset page (see docstring)."
            )

        split_list = np.loadtxt(str(root / split_file_name), dtype=np.int32)
        for i in range(len(flows)):
            split_id = split_list[i]
            if (split == "train" and split_id == 1) or (split == "val" and split_id == 2):
                self._flow_list += [flows[i]]
                self._image_list += [[images[2 * i], images[2 * i + 1]]]