Remove rotation effect when drawing a square grid of MxM nodes in networkx using grid_2d_graph

Question

I need to generate a regular graph (also known as lattice network) which has 100x100 nodes. I started off with drawing a 10x10 graph with the follo

Answer 1

By default, networkx.draw uses a spring layout. Instead, you can provide your own positions with parameter pos. This is actually really simple, since the labels of nodes given networkx.grid_2d_graph actually are a (row, column) tuple:

>>> G=nx.grid_2d_graph(2,2)
[(0, 1), (1, 0), (0, 0), (1, 1)]

Thus you can use a node's name as its position. So you just need to create a dictionary mapping nodes to themselves, and pass that as the position.

pos = dict( (n, n) for n in G.nodes() )

However, since you also want to add node labels, you should use networkx.draw_networkx, which takes a dictionary of custom labels as an optional parameter. You'll need a dictionary mapping nodes to their new labels. Since NetworkX gives each node the label (row, column) by default, we can just label each node with row * 10 + column:

labels = dict( ((i, j), i * 10 + j) for i, j in G.nodes() )

Putting it all together, you get the following code which yields the graph below:

import networkx as nx
import matplotlib.pyplot as plt

N = 10
G=nx.grid_2d_graph(N,N)
pos = dict( (n, n) for n in G.nodes() )
labels = dict( ((i, j), i * 10 + j) for i, j in G.nodes() )
nx.draw_networkx(G, pos=pos, labels=labels)

plt.axis('off')
plt.show()

EDIT

Using the suggestion from @AbdallahSobehy, we can label the nodes from left to right and top to bottom.

labels = dict( ((i, j), i + (N-1-j) * 10 ) for i, j in G.nodes() )