def test_set_scalar_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(np.zeros((10, 10))))
    orig_X_val = adata.X.copy()
    subset_idx = slice_subset(adata.obs_names)

    adata_subset = adata[subset_idx, :]

    adata_subset.X = 1

    assert adata_subset.is_view
    assert np.all(asarray(adata[subset_idx, :].X) == 1)

    assert asarray((orig_X_val != adata.X)).sum() == mul(*adata_subset.shape)
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")))