从距离矩阵绘制图形或网络？

Question

我正在尝试绘制/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其节点的线和列.

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] ]

我正在寻找从这样的(更大的:数千列和线)距离矩阵绘制/绘制2d网络:节点'a'通过边缘深度0.3,节点'c'和'd链接到节点'b' '将被边缘深度0.1绑定.我可以使用哪些工具/库(距离矩阵可以转换成numpy矩阵)来获得这种网络的草图/图形投影？(pandas,matplotlib,igraph,......？)和一些导致快速做到这一点(我不会定义我的自我Tkinter功能来做那个;-))？谢谢你的回答.

Answer 1

的graphviz的程序neato 试图尊重边缘长度.道格显示了一种neato利用networkx进行利用的方法,如下所示:

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')

产量

如果要生成点文件,可以使用

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

产量

strict graph {
    graph [bb="0,0,226.19,339.42"];
    node [color=red,
        label="\N",
        style=filled
    ];
    edge [color=blue,
        width=2.0
    ];
    B    [height=0.5,
        pos="27,157.41",
        width=0.75];
    D    [height=0.5,
        pos="69,303.6",
        width=0.75];
    B -- D   [len=2.0,
        pos="32.15,175.34 40.211,203.4 55.721,257.38 63.808,285.53"];
    A    [height=0.5,
        pos="199.19,18",
        width=0.75];
    B -- A   [len=3.0,
        pos="44.458,143.28 77.546,116.49 149.02,58.622 181.94,31.965"];
    C    [height=0.5,
        pos="140.12,321.42",
        width=0.75];
    B -- C   [len=9.0,
        pos="38.469,174.04 60.15,205.48 106.92,273.28 128.62,304.75"];
    D -- A   [len=7.0,
        pos="76.948,286.17 100.19,235.18 167.86,86.729 191.18,35.571"];
    D -- C   [len=1.0,
        pos="94.274,309.94 100.82,311.58 107.88,313.34 114.45,314.99"];
    A -- C   [len=4.0,
        pos="195.67,36.072 185.17,90.039 154.1,249.6 143.62,303.45"];
}

png然后可以使用该graphviz neato程序生成该文件:

neato -Tpng -o /tmp/out.png /tmp/out.dot 

Answer 2

您可以使用networkx包,它可以很好地解决这类问题.调整矩阵以删除一个简单的numpy数组,如下所示:

DistMatrix =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] ])

然后导入networkx并使用它

import networkx as nx
G = G=nx.from_numpy_matrix(DistMatrix)
nx.draw(G)

如果你想绘制图形的加权版本,你必须指定每条边的颜色(至少,我找不到更自动化的方法):

nx.draw(G,edge_color = [ i[2]['weight'] for i in G.edges(data=True) ], edge_cmap=cm.winter )