从距离矩阵绘制图形或网络？ [英] Drawing a graph or a network from a distance matrix?

问题描述

我试图绘制/绘制（matplotlib或其他python库）一个大距离矩阵的2D网络，其中距离将是草绘网络的边缘以及线和节点的节点。

  DistMatrix = 
 ['a'，'b'，'c'，'d']，
 ['a' ，0,0.3,0.4,0.7]，
 ['b'，0.3,0,0.9,0.2]，
 ['c'，0.4,0.9,0,0.1]，
 ['d'，0.7,0.2,0.1,0]] 
  

我正在寻找素描/从这样的（更大的：数千列和线）距离矩阵绘制2D网络：节点'a'通过0.3的边缘深度链接到节点'b'，节点'c'和'd'将被边缘深度为0.1。
我可以使用哪些工具/库（距离矩阵可以转换为numpy矩阵）以获得此类网络的草图/图形投影？ （熊猫，matplotlib，igraph，...？）和一些导致做到这一点（我不会定义自己的Tkinter函数来做到这一点;-)）？
感谢您收到的答案。 graphviz 程序 neato 试图尊重边缘长度。 道格显示一种方式利用 neato 使用

  import networkx as nx 
 import numpy as np 
 import string 
 
 dt = [（'len'，float）] 
 A = np.array（[（0， 0.3,0.4,0.7），
（0.3,0,0.9,0.2），
（0.4,0.9,0,0.1），
（0.7,0.2,0.1,0）$ b （b））* 10 
 A = A.view（dt）
 
 G = nx.from_numpy_matrix（A）
 G = nx.relabel_nodes（G，dict（zip range（len（G.nodes（））），string.ascii_uppercase）））
 
 G = nx.drawing.nx_agraph.to_agraph（G）
 
 G.node_attr。更新（color =red，style =filled）
 G.edge_attr.update（color =blue，width =2.0）
 
 G.draw（'/ tmp / out.png'，format ='png'，prog ='neato'）
  

/ p>

I'm trying to plot/sketch (matplotlib or other python library) a 2D network of a big distance matrix where distances would be the edges of the sketched network and the line and column its nodes.

DistMatrix =
[       'a',   'b',     'c',    'd'],
['a',   0,      0.3,    0.4,    0.7],
['b',   0.3,    0,      0.9,    0.2],
['c',   0.4,    0.9,    0,      0.1],
['d',   0.7,    0.2,    0.1,    0] ]

I'm searching to sketch/plot the 2d network from such (bigger: thousand of columns and lines) distance matrix: node 'a' is linked to node 'b' by an edge depth of 0.3, nodes 'c' and 'd' would be tied by an edge depth of 0.1. What are the tools/libraries I can used (distance matrix can be converted into numpy matrix) to get the sketch/graphical projection of such network? (pandas, matplotlib, igraph,...?) and some leads to do that quickly (I would not define my self Tkinter function to do that ;-) ) ? thanks for your incoming answers.

解决方案

The graphviz program neato tries to respect edge lengths. doug shows a way to harness neato using networkx like this:

import networkx as nx
import numpy as np
import string

dt = [('len', float)]
A = np.array([(0, 0.3, 0.4, 0.7),
               (0.3, 0, 0.9, 0.2),
               (0.4, 0.9, 0, 0.1),
               (0.7, 0.2, 0.1, 0)
               ])*10
A = A.view(dt)

G = nx.from_numpy_matrix(A)
G = nx.relabel_nodes(G, dict(zip(range(len(G.nodes())),string.ascii_uppercase)))    

G = nx.drawing.nx_agraph.to_agraph(G)

G.node_attr.update(color="red", style="filled")
G.edge_attr.update(color="blue", width="2.0")

G.draw('/tmp/out.png', format='png', prog='neato')

yields

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