Let's say I have to initialise the bi-directional edges for the following graph between the nodes:
I can easily do this using the following code:
import numpy as np
node_num = 3
graph = np.ones([node_num, node_num]) - np.eye(node_num)
Now I am extending this graph in the following way:
What is the simple and efficient way to make it code for this graph?
Assuming you're looking for an adjacency matrix, you could use:
out = np.block([
[1 - np.eye(3), np.eye(3) ],
[ np.eye(3), np.zeros((3, 3))]
]).astype(int)
out:
array([[0, 1, 1, 1, 0, 0], # A
[1, 0, 1, 0, 1, 0], # B
[1, 1, 0, 0, 0, 1], # C
[1, 0, 0, 0, 0, 0], # BC
[0, 1, 0, 0, 0, 0], # AB
[0, 0, 1, 0, 0, 0]]) # AB(red)
but I would suggest you just initialize it as the outputted adjacency matrix. I would only use a short one liner for very simple graphs like your first image, not the second.
(A, B, C, D, E, AB, AC, AD, AE, BC, BD, BE, CD, CE, DE) it cannot work.n nodes.
n nodes? A central graph fully connected graph with n / 2 nodes, each of which has one more node connected to itself but not anywhere else?