使用grid_2d_graph在网络x中绘制MxM节点的方形网格时移除旋转效果 [英] Remove rotation effect when drawing a square grid of MxM nodes in networkx using grid_2d_graph

问题描述

我需要生成一个正则图（也称为格子网络），它具有 100x100 节点。我开始用以下代码绘制 10x10 图：

 从numpy导入导入numpy 
 * 
从networkx导入导入networkx为nx 
 * 
导入matplotlib.pyplot作为plt 
 
 G = nx.grid_2d_graph（ 10,10）
 nx.draw（G）
 
 plt.axis（'off'）
 plt.show（）
  
 
 
 
但我得到的是这样的： 
 
 
  
 
 
 
 另外，我需要为每个节点提供其ID，范围从0到9999 （对于100x100网络）。任何想法将不胜感激！
解决方案
默认情况下， 
 
 
 
 编辑 
 
 
 
使用@AbdallahSobehy的建议，我们可以从左到右和从上到下标注节点。
 
 
 <$对于在G.nodes（）中的i，j）
，（p（p（i，j），i +（N-1-j）* 10） code> 

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 following code:

import numpy
from numpy import *
import networkx as nx
from networkx import *
import matplotlib.pyplot as plt

G=nx.grid_2d_graph(10,10)        
nx.draw(G)

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

but what I get is this:

Is there any way of getting rid of this sort of rotation effect the output has? My final network must look like a chess table, just like this (please ignore the lables):

Also, I need to give each node its ID, ranging from 0 to 9999 (in the case of the 100x100 network). Any idea will be much appreciated!

解决方案

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() )

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