def test_normalize_diagraph():
    num_node = 15
    self_link = [(i, i) for i in range(num_node)]
    neighbor_link = [(0, 1), (1, 2), (3, 4), (4, 5), (2, 8), (8, 7), (7, 6), (8, 12), (12, 9), (9, 10), (10, 11), (9, 3), (12, 13), (13, 14)]
    edge = (self_link + neighbor_link)
    print('Edge: \n{}\n'.format(edge))
    hop_dis = get_hop_distance(num_node, edge, max_hop=1)
    print('Hop_dis: \n{}\n'.format(hop_dis))
    max_hop = 1
    dilation = 1
    valid_hop = range(0, (max_hop + 1), dilation)
    print('Valid_hop: \n{}\n'.format(valid_hop))
    adjacency = np.zeros((num_node, num_node))
    for hop in valid_hop:
        adjacency[(hop_dis == hop)] = 1
    print('Adjacency matrix: \n{}\n'.format(adjacency))
    normalize_adjacency = normalize_digraph(adjacency)
    print('Normalized adjacency matrix: \n{}\n'.format(normalize_adjacency))
    return
def test_normalize_diagraph():
    num_node = 15
    self_link = [(i, i) for i in range(num_node)]
    neighbor_link = [(0, 1), (1, 2), (3, 4), (4, 5), (2, 8), (8, 7), (7, 6), (8, 12), (12, 9), (9, 10), (10, 11), (9, 3), (12, 13), (13, 14)]
    edge = (self_link + neighbor_link)
    print('Edge: \n{}\n'.format(edge))
    hop_dis = get_hop_distance(num_node, edge, max_hop=1)
    print('Hop_dis: \n{}\n'.format(hop_dis))
    max_hop = 1
    dilation = 1
    valid_hop = range(0, (max_hop + 1), dilation)
    print('Valid_hop: \n{}\n'.format(valid_hop))
    adjacency = np.zeros((num_node, num_node))
    for hop in valid_hop:
        adjacency[(hop_dis == hop)] = 1
    print('Adjacency matrix: \n{}\n'.format(adjacency))
    normalize_adjacency = normalize_digraph(adjacency)
    print('Normalized adjacency matrix: \n{}\n'.format(normalize_adjacency))
    return