Plotting in numpy a graph using the two lowest eigenvalues and eigenvectors

Question

How do I use the eigenvectors corresponding to the two lowest eigenvalues (different from 0) as the x,y coordinates to plot the graph?

I have arrays of eigenvalues and eigenvectors from the laplacian of a graph of nodes. I want to do something similar to the following link that is in MATLAB, but in Python. Also, instead of just the Fielder vector, I also want the next vector larger than the Fielder as well:

https://www.mathworks.com/examples/matlab/mw/matlab-ex64540792-partition-graph-with-laplacian-matrix

Thanks in advance!

Can you show the code you use to get the eigenvectors? – Joel Nov 29 '16 at 00:59 — Joel, Nov 29 '16 at 00:59

score 0 · Accepted Answer · edited May 23 '17 at 12:07

This answer assumes you've already got nodes in a list nodelist and two vectors vec1 and vec2 which are in the same order.

Networkx uses a dict (usually called pos) for which pos[u] is the (x,y) coordinates of the node u.

import networkx as nx

#your code here to define network and find the vectors.  
#Please edit a simple version of this code into your question so I can
#add it here.

pos = {node:(x,y) for node, x, y in zip(nodelist, vec1, vec2)}
nx.draw_networkx(G, pos=pos)

In defining pos, I've used a dict comprehension and zip.

Plotting in numpy a graph using the two lowest eigenvalues and eigenvectors

1 Answers1