s can be obtained with `nonzero`:

    >>> np.nonzero(mask)
    (array([0, 1]), array([1, 0]))

    The test can also be inverted:

    >>> mask = np.isin(element, test_elements, invert=True)
    >>> mask
    array([[ True, False],
           [False,  True]])
    >>> element[mask]
    array([0, 6])

    Because of how `array` handles sets, the following does not
    work as expected:

    >>> test_set = {1, 2, 4, 8}
    >>> np.isin(element, test_set)
    array([[False, False],
           [False, False]])

    Casting the set to a list gives the expected result:

    >>> np.isin(element, list(test_set))
    array([[False,  True],
           [ True, False]])
    )