有没有办法保证NetworkX的分层输出? [英] Is there a way to guarantee hierarchical output from NetworkX?

问题描述

我正在尝试生成树结构的流程图.我已经可以使用networkx创建代表性图形，但是我需要一种在输出图时显示树结构的方法.我正在使用matplotlib.pylab绘制图形.

I'm trying to produce a flow diagram of a tree structure. I've been able to create representative graphs with networkx, but I need a way to show the tree structure when I output a plot. I'm using matplotlib.pylab to plot the graph.

我需要以类似于此处.尽管我没有子图.

I need to show the data in a structure similar to what is shown here. Although I don't have sub-graphs.

如何保证这样的结构?

不信者的例子:

我已经可以使用pylab和graphviz来显示图形，但是都没有提供我要寻找的树结构.我已经尝试了networkx必须提供的所有布局，但是都没有显示层次结构.我只是不确定如果需要使用权重，可以使用哪种 options/mode 来赋予它 OR .任何建议都会帮助一堆.

I've been able to show the graphs with pylab and graphviz, but neither offer the tree structure I'm looking for. I've tried every layout networkx has to offer, but none of them show a hierarchy. I've just not sure what options/mode to give it OR if I need to use weights. Any suggestions would help a bunch.

@jterrace:

@jterrace:

以下是我用来制作上述情节的粗略概述.我添加了一些标签，但除此之外，都是相同的.

Here's a rough outline of what I used to produce the plots above. I've added some labels, but other than that it's the same.

import networkx as nx
import matplotlib.pyplot as plt
G = nx.Graph()

G.add_node("ROOT")

for i in xrange(5):
    G.add_node("Child_%i" % i)
    G.add_node("Grandchild_%i" % i)
    G.add_node("Greatgrandchild_%i" % i)

    G.add_edge("ROOT", "Child_%i" % i)
    G.add_edge("Child_%i" % i, "Grandchild_%i" % i)
    G.add_edge("Grandchild_%i" % i, "Greatgrandchild_%i" % i)

plt.title("draw_networkx")
nx.draw_networkx(G)

plt.show()

推荐答案

如果使用有向图，则Graphviz点布局将对树执行所需的操作.这是类似于上述解决方案的一些代码，展示了如何实现

If you use a directed graph then the Graphviz dot layout will do something like you want with the tree. Here is some code similar to the above solutions that shows how to do that

import networkx as nx
from networkx.drawing.nx_agraph import graphviz_layout
import matplotlib.pyplot as plt
G = nx.DiGraph()

G.add_node("ROOT")

for i in range(5):
    G.add_node("Child_%i" % i)
    G.add_node("Grandchild_%i" % i)
    G.add_node("Greatgrandchild_%i" % i)

    G.add_edge("ROOT", "Child_%i" % i)
    G.add_edge("Child_%i" % i, "Grandchild_%i" % i)
    G.add_edge("Grandchild_%i" % i, "Greatgrandchild_%i" % i)

# write dot file to use with graphviz
# run "dot -Tpng test.dot >test.png"
nx.nx_agraph.write_dot(G,'test.dot')

# same layout using matplotlib with no labels
plt.title('draw_networkx')
pos=graphviz_layout(G, prog='dot')
nx.draw(G, pos, with_labels=False, arrows=False)
plt.savefig('nx_test.png')

已更新

这是为networkx-2.0更新的版本(并且在即将发布的networkx-2.1中也绘制了箭头).

Here is a version updated for networkx-2.0 (and with upcoming networkx-2.1 draws arrows too).

import networkx as nx
from networkx.drawing.nx_agraph import write_dot, graphviz_layout
import matplotlib.pyplot as plt
G = nx.DiGraph()

G.add_node("ROOT")

for i in range(5):
    G.add_node("Child_%i" % i)
    G.add_node("Grandchild_%i" % i)
    G.add_node("Greatgrandchild_%i" % i)

    G.add_edge("ROOT", "Child_%i" % i)
    G.add_edge("Child_%i" % i, "Grandchild_%i" % i)
    G.add_edge("Grandchild_%i" % i, "Greatgrandchild_%i" % i)

# write dot file to use with graphviz
# run "dot -Tpng test.dot >test.png"
write_dot(G,'test.dot')

# same layout using matplotlib with no labels
plt.title('draw_networkx')
pos =graphviz_layout(G, prog='dot')
nx.draw(G, pos, with_labels=False, arrows=True)
plt.savefig('nx_test.png')

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