def fig16():
    """The network shown in Figure 5B of the 2014 IIT 3.0 paper."""
    tpm = np.array([
        [0, 0, 0, 0, 0, 0, 0],
        [0, 0, 1, 0, 1, 0, 0],
        [1, 0, 1, 0, 0, 0, 0],
        [1, 0, 0, 0, 1, 0, 0],
        [1, 0, 0, 0, 0, 0, 0],
        [1, 0, 1, 0, 1, 0, 0],
        [1, 0, 1, 0, 0, 0, 0],
        [1, 0, 0, 0, 1, 0, 0],
        [0, 0, 0, 1, 1, 0, 0],
        [0, 0, 1, 1, 1, 0, 0],
        [1, 0, 1, 1, 1, 0, 0],
        [1, 0, 0, 1, 1, 0, 0],
        [1, 0, 0, 1, 1, 0, 0],
        [1, 1, 1, 1, 1, 0, 0],
        [1, 0, 1, 1, 1, 0, 0],
        [1, 1, 0, 1, 1, 0, 0],
        [0, 0, 0, 1, 1, 0, 0],
        [0, 0, 1, 1, 1, 0, 0],
        [1, 0, 1, 1, 1, 0, 0],
        [1, 0, 0, 1, 1, 0, 0],
        [1, 0, 0, 1, 1, 0, 0],
        [1, 0, 1, 1, 1, 0, 0],
        [1, 0, 1, 1, 1, 0, 0],
        [1, 0, 0, 1, 1, 0, 0],
        [0, 0, 0, 1, 1, 0, 0],
        [0, 0, 1, 1, 1, 0, 0],
        [1, 0, 1, 1, 1, 0, 0],
        [1, 0, 0, 1, 1, 0, 0],
        [1, 0, 0, 1, 1, 0, 0],
        [1, 1, 1, 1, 1, 0, 0],
        [1, 0, 1, 1, 1, 0, 0],
        [1, 1, 0, 1, 1, 0, 0],
        [0, 0, 0, 0, 0, 1, 0],
        [0, 0, 1, 0, 1, 1, 0],
        [1, 0, 1, 0, 0, 1, 0],
        [1, 0, 0, 0, 1, 1, 0],
        [1, 0, 0, 0, 0, 1, 0],
        [1, 0, 1, 0, 1, 1, 0],
        [1, 0, 1, 0, 0, 1, 0],
        [1, 0, 0, 0, 1, 1, 0],
        [0, 0, 0, 1, 1, 1, 0],
        [0, 0, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 1, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 1, 0, 1, 1, 1, 0],
        [0, 0, 0, 1, 1, 1, 0],
        [0, 0, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [0, 0, 0, 1, 1, 1, 0],
        [0, 0, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 1, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 1, 0, 1, 1, 1, 0],
        [0, 0, 0, 0, 0, 1, 0],
        [0, 0, 1, 0, 1, 1, 0],
        [1, 0, 1, 0, 0, 1, 0],
        [1, 0, 0, 0, 1, 1, 0],
        [1, 0, 0, 0, 0, 1, 0],
        [1, 0, 1, 0, 1, 1, 0],
        [1, 0, 1, 0, 0, 1, 0],
        [1, 0, 0, 0, 1, 1, 0],
        [0, 0, 0, 1, 1, 1, 0],
        [0, 0, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 1, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 1, 0, 1, 1, 1, 0],
        [0, 0, 0, 1, 1, 1, 0],
        [0, 0, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [0, 0, 0, 1, 1, 1, 0],
        [0, 0, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 0, 0, 1, 1, 1, 0],
        [1, 1, 1, 1, 1, 1, 0],
        [1, 0, 1, 1, 1, 1, 0],
        [1, 1, 0, 1, 1, 1, 0],
        [0, 0, 0, 0, 0, 1, 1],
        [0, 0, 1, 0, 1, 1, 1],
        [1, 0, 1, 0, 0, 1, 1],
        [1, 0, 0, 0, 1, 1, 1],
        [1, 0, 0, 0, 0, 1, 1],
        [1, 0, 1, 0, 1, 1, 1],
        [1, 0, 1, 0, 0, 1, 1],
        [1, 0, 0, 0, 1, 1, 1],
        [0, 0, 0, 1, 1, 1, 1],
        [0, 0, 1, 1, 1, 1, 1],
        [1, 0, 1, 1, 1, 1, 1],
        [1, 0, 0, 1, 1, 1, 1],
        [1, 0, 0, 1, 1, 1, 1],
        [1, 1, 1, 1, 1, 1, 1],
        [1, 0, 1, 1, 1, 1, 1],
        [1, 1, 0, 1, 1, 1, 1],
        [0, 0, 0, 1, 1, 1, 1],
        [0, 0, 1, 1, 1, 1, 1],
        [1, 0, 1, 1, 1, 1, 1],
        [1, 0, 0, 1, 1, 1, 1],
        [1, 0, 0, 1, 1, 1, 1],
        [1, 0, 1, 1, 1, 1, 1],
        [1, 0, 1, 1, 1, 1, 1],
        [1, 0, 0, 1, 1, 1, 1],
        [0, 0, 0, 1, 1, 1, 1],
        [0, 0, 1, 1, 1, 1, 1],
        [1, 0, 1, 1, 1, 1, 1],
        [1, 0, 0, 1, 1, 1, 1],
        [1, 0, 0, 1, 1, 1, 1],
        [1, 1, 1, 1, 1, 1, 1],
        [1, 0, 1, 1, 1, 1, 1],
        [1, 1, 0, 1, 1, 1, 1]
    ])
    cm = np.array([
        [0, 1, 1, 0, 1, 0, 0],
        [1, 0, 1, 0, 0, 0, 0],
        [1, 1, 0, 0, 0, 0, 0],
        [0, 1, 0, 1, 1, 0, 0],
        [0, 0, 0, 1, 1, 0, 0],
        [0, 0, 0, 0, 0, 1, 1],
        [0, 0, 0, 0, 0, 1, 1]
    ])
    return Network(tpm, cm=cm, node_labels=LABELS[:tpm.shape[1]])
The network shown in Figure 5B of the 2014 IIT 3.0 paper.