def test_set_varm(adata):
    init_hash = joblib.hash(adata)

    dim0_size = np.random.randint(2, adata.shape[1] - 1)
    dim1_size = np.random.randint(1, 99)
    orig_varm_val = adata.varm["o"].copy()
    subset_idx = np.random.choice(adata.var_names, dim0_size, replace=False)

    subset = adata[:, subset_idx]
    assert subset.is_view
    subset.varm = dict(o=np.ones((dim0_size, dim1_size)))
    assert not subset.is_view
    assert np.all(orig_varm_val == adata.varm["o"])  # Checking for mutation
    assert np.all(subset.varm["o"] == np.ones((dim0_size, dim1_size)))

    subset = adata[:, subset_idx]
    subset_hash = joblib.hash(subset)
    with pytest.raises(ValueError):
        subset.varm = dict(o=np.ones((dim0_size + 1, dim1_size)))
    with pytest.raises(ValueError):
        subset.varm = dict(o=np.ones((dim0_size - 1, dim1_size)))
    # subset should not be changed by failed setting
    assert subset_hash == joblib.hash(subset)
    assert init_hash == joblib.hash(adata)
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)