NetworkX 节点标签相对位置

Question

我正在努力解决以下问题。根据之前完成的分类，我想绘制一个包含大约 100 个节点的圆形图，我必须在其中手动定位它们。这些节点有一个指定的标签来描述它们，文本长度不同，我想把这个标签放在节点旁边。下图是我想要得到的（我画蓝色圆圈只是为了表明标签在外围完全对齐）： https://i.stack.imgur.com/Qre0Z.png

到目前为止我只画了这个：https://i.stack.imgur.com/U7bZG.png

这是 MWE：

import numpy as np
import networkx as nx
import matplotlib.pyplot as plt

n = 7
G = nx.complete_graph(n)
node_list = sorted(G.nodes())
angle = []
angle_dict = {}
for i, node in zip(xrange(n),node_list):
    theta = 2.0*np.pi*i/n
    angle.append((np.cos(theta),np.sin(theta)))
    angle_dict[node] = theta
pos = {}
for node_i, node in enumerate(node_list):
    pos[node] = angle[node_i]

labels = {0:'zero',1:'oneone',2:'twotwo',3:'threethreethree',4:'fourfourfourfour',5:'fivefivefivefivefive',6:'sixsixsixsixsixsix'}

# figsize is intentionally set small to condense the graph
f = plt.figure(figsize=(2,2))
r = f.canvas.get_renderer()
plt.axis('equal')
nx.draw(G,pos=pos,with_labels=True)
description = nx.draw_networkx_labels(G,pos,labels=labels)
for node, t in description.items():
    t.set_rotation(angle_dict[node]*360.0/(2.0*np.pi))
plt.show()

我想我必须添加和玩

x, y = t.get_position()
bb = t.get_window_extent(renderer=r)
radius = 1.0+2.0*bb.width/r.width
t.set_position((radius*x,radius*y))

在我设置标签旋转的循环中。但是，我不知道如何正确设置它以及如何避免裁剪 canvas.

Answer 1

为了在轴外显示标签，您需要使轴比图形小，例如通过在轴周围引入较大的边距。您还需要设置文本的剪辑状态，这样它就不会被轴切断。

根据边界框的宽度定位标签需要先将边界框从显示坐标转换为数据坐标。

完整的解决方案：

import numpy as np
import networkx as nx
import matplotlib.pyplot as plt

n = 7
G = nx.complete_graph(n)
node_list = sorted(G.nodes())
angle = []
angle_dict = {}
for i, node in zip(xrange(n),node_list):
    theta = 2.0*np.pi*i/n
    angle.append((np.cos(theta),np.sin(theta)))
    angle_dict[node] = theta
pos = {}
for node_i, node in enumerate(node_list):
    pos[node] = angle[node_i]

labels = {0:'zero',1:'oneone',2:'twotwo',3:'threethreethree',4:'fourfourfourfour',5:'fivefivefivefivefive',6:'sixsixsixsixsixsix'}

# figsize is intentionally set small to condense the graph
fig, ax = plt.subplots(figsize=(5,5))
margin=0.33
fig.subplots_adjust(margin, margin, 1.-margin, 1.-margin)
ax.axis('equal')

nx.draw(G,pos=pos,with_labels=True, ax=ax)
description = nx.draw_networkx_labels(G,pos,labels=labels)

r = fig.canvas.get_renderer()
trans = plt.gca().transData.inverted()
for node, t in description.items():
    bb = t.get_window_extent(renderer=r)
    bbdata = bb.transformed(trans)
    radius = 1.2+bbdata.width/2.
    position = (radius*np.cos(angle_dict[node]),radius* np.sin(angle_dict[node]))
    t.set_position(position)
    t.set_rotation(angle_dict[node]*360.0/(2.0*np.pi))
    t.set_clip_on(False)

plt.show()

NetworkX 节点标签相对位置

NetworkX node labels relative position

python

graph

matplotlib

networkx