Python中生成特定的邻接矩阵

Question

I have a.network with nodes and vertices and the following numbering scheme. I want to generate an adjacency matrix A for the nodes 0,1 as shown below. I tried to do using networkx . I present the current and expected outputs.

import networkx as nx
N=2
def pos():
    x, y = 1, N + 3 - 1
    for _ in range(N):
        yield (x, y)
        y -= (x + 2) // (N+1 )
        x = (x + 2) % (N+1)

G = nx.Graph()
it_pos = pos()
for u in range(N):
    G.add_node(u+1, pos=next(it_pos))
    if u % (2 * N) < N:
        for v in (u - 2 * N, u - N, u - N):
            if G.has_node(v + 1):
                G.add_edge(u + 2, v + 2)
    elif u % (2 * N) == N:
        G.add_edge(u + 1, u - N + 1)
    elif u % (2 * N + 1) < 2 * N:
        for v in (u - 1, u - N, u - N):
            G.add_edge(u + 1, v + 1)
    else:
        for v in (u - 1, u - N - 1):
            G.add_edge(u + 1, v + 1)

nx.draw(G, nx.get_node_attributes(G, 'pos'), with_labels=True, font_weight='bold')  
Nodes=len(G.nodes)
A=nx.adjacency_matrix(G).todense()

The current output is

A=matrix([[0., 0.],
        [0., 0.]])

The expected output is

Answer 1

You want the adjacency matrix between node and its edges, but the function you are using looks for neighbouring nodes.

In order to build your.network and get your matrix, you could do the following:

import networkx as nx
import numpy as np
import pandas as pd

# build the network with relevant edges
G = nx.Graph()
points = {
    0: (1, 1), 1: (2, 1),
    'a':(1, 2), 'b':(2, 2),
    'c':(0, 1), 'd':(3, 1),
    'e':(1, 0), 'f':(2, 0)
}
for key, pos in points.items():
    G.add_node(key, pos=pos)
G.add_edge('a', 0, name=0)
G.add_edge('b', 1, name=1)
G.add_edge('c', 0, name=2)
G.add_edge(0, 1, name=3)
G.add_edge(1, 'd', name=4)
G.add_edge(0, 'e', name=5)
G.add_edge(1, 'f', name=6)

# find connected edges to nodes 0 and 1
my_nodes = [0, 1]  # could be more here
edges = {
    node: [G.get_edge_data(*edge)['name'] for edge in G.edges(node)]
    for node in my_nodes
}
# build matirx
mat = np.zeros((len(my_nodes), 7), dtype=np.uint8)
for i, node in enumerate(my_nodes)):
    mat[i, edges[node]] = 1
    mat[i, edges[node]] = 1
A = pd.DataFrame(mat)
A

Edit: generalize the connection search.

Answer 2

You can implement the matrix in Python using a nested list:

A = [[1, 0, 1, 1, 0, 1, 0], [0, 1, 0, 1, 1, 0, 1]]