def test_negative_scalar_index(adata, index: int, obs: bool):
    pos_index = index + (adata.n_obs if obs else adata.n_vars)

    if obs:
        adata_pos_subset = adata[pos_index]
        adata_neg_subset = adata[index]
    else:
        adata_pos_subset = adata[:, pos_index]
        adata_neg_subset = adata[:, index]

    np.testing.assert_array_equal(
        adata_pos_subset.obs_names, adata_neg_subset.obs_names
    )
    np.testing.assert_array_equal(
        adata_pos_subset.var_names, adata_neg_subset.var_names
    )
def _read_flo(file_name):
    """Read .flo file in Middlebury format"""
    # Code adapted from:
    # http://stackoverflow.com/questions/28013200/reading-middlebury-flow-files-with-python-bytes-array-numpy
    # Everything needs to be in little Endian according to
    # https://vision.middlebury.edu/flow/code/flow-code/README.txt
    with open(file_name, "rb") as f:
        magic = np.fromfile(f, "c", count=4).tobytes()
        if magic != b"PIEH":
            raise ValueError("Magic number incorrect. Invalid .flo file")

        w = int(np.fromfile(f, "<i4", count=1))
        h = int(np.fromfile(f, "<i4", count=1))
        data = np.fromfile(f, "<f4", count=2 * w * h)
        return data.reshape(h, w, 2).transpose(2, 0, 1)