Python Nympy 中 Graph 的邻接矩阵

Question

I need to make an adjacency metrics

I have the edges information.

edges = numpy.array([[0,1],[0,3],[1,2],[1,4],[2,5],[3,4],[3,5],[4,5]])

I need a python code to generate the adjacency metrics using NumPy only from the edges information. Can someone help?

Answer 1

It depends what type of adjacency matrix you want, but here's an example with 0 for not connected and 1 for connected, rows are from and columns are to.

import numpy

edges = numpy.array([[0,1],[0,3],[1,2],[1,4],[2,5],[3,4],[3,5],[4,5]])

matrix = numpy.zeros((edges.max()+1, edges.max()+1))
matrix[edges[:,0], edges[:,1]] = 1

gives

array([[0., 1., 0., 1., 0., 0.],
       [0., 0., 1., 0., 1., 0.],
       [0., 0., 0., 0., 0., 1.],
       [0., 0., 0., 0., 1., 1.],
       [0., 0., 0., 0., 0., 1.],
       [0., 0., 0., 0., 0., 0.]])

If you want the connections to be bidirectional (ie. 0->1 also connects 1->0), then add another line of code to do the reverse connection.

import numpy

edges = numpy.array([[0,1],[0,3],[1,2],[1,4],[2,5],[3,4],[3,5],[4,5]])

matrix = numpy.zeros((edges.max()+1, edges.max()+1))
matrix[edges[:,0], edges[:,1]] = 1
matrix[edges[:,1], edges[:,0]] = 1

gives

array([[0., 1., 0., 1., 0., 0.],
       [1., 0., 1., 0., 1., 0.],
       [0., 1., 0., 0., 0., 1.],
       [1., 0., 0., 0., 1., 1.],
       [0., 1., 0., 1., 0., 1.],
       [0., 0., 1., 1., 1., 0.]])

Answer 2

The easiest way to get the job done would be using the NetworkX package (if you are allowed to).

In [72]: import networkx as nx

In [73]: edges = [[0, 1], [0, 3], [1, 2], [1, 4], [2, 5], [3, 4], [3, 5], [4, 5]]

In [74]: nodes = sorted(set(node for edge in edges for node in edge))

In [75]: G = nx.Graph()

In [76]: G.add_nodes_from(nodes)

In [77]: G.add_edges_from(edges)

In [78]: A = nx.adjacency_matrix(G)

In [79]: A.toarray()
Out[79]: 
array([[0, 1, 0, 1, 0, 0],
       [1, 0, 1, 0, 1, 0],
       [0, 1, 0, 0, 0, 1],
       [1, 0, 0, 0, 1, 1],
       [0, 1, 0, 1, 0, 1],
       [0, 0, 1, 1, 1, 0]], dtype=int32)