def METHOD_NAME():
    data = np.ones(63,dtype=int)
    rows = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 
                2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5,
                6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8, 9, 9,
                9, 10, 10, 10, 10, 10, 11, 11, 11, 11, 
                12, 12, 12, 13, 13, 13, 13, 14, 14, 14,
                14, 15, 15, 15, 15, 15])
    cols = np.array([0, 2, 5, 8, 10, 1, 3, 9, 11, 0, 2,
                7, 10, 1, 3, 11, 4, 6, 12, 14, 0, 7, 13, 
                15, 4, 6, 14, 2, 5, 7, 15, 0, 8, 10, 13,
                1, 9, 11, 0, 2, 8, 10, 15, 1, 3, 9, 11,
                4, 12, 14, 5, 8, 13, 15, 4, 6, 12, 14,
                5, 7, 10, 13, 15])
    graph = coo_matrix((data, (rows,cols))).tocsr()
    perm = reverse_cuthill_mckee(graph)
    correct_perm = np.array([12, 14, 4, 6, 10, 8, 2, 15,
                0, 13, 7, 5, 9, 11, 1, 3])
    assert_equal(perm, correct_perm)