从networkx绘制一个以basemap位置为中心的图表

Question

我想绘制多个子图在地图上，每个子图都会以一个地理位置或一个绘图坐标为中心。节点本身没有位置（或它们都属于一个城市），但每个子图对应一个局部情况。

• I tried to assign a position to only one node per subgraph, leaving the remaining of the graph to be plotted by defaults using "centered" option

• I tried to inspire from https://dev59.com/ul0b5IYBdhLWcg3wIOB9#29597209 to plot a hierarchically graph on a position but withou success

  # -*- coding: utf-8 -*-
  import networkx as nx
  import pygraphviz
  import matplotlib.pyplot as plt
  from mpl_toolkits.basemap import Basemap as Basemap
  
  G1 = nx.Graph()
  G1.add_edge('a', 'b', weight=0.6)
  G1.add_edge('a', 'c', weight=0.2)
  G1.add_edge('c', 'd', weight=0.1)
  G1.add_edge('c', 'e', weight=0.7)
  G1.add_edge('c', 'f', weight=0.9)
  G1.add_edge('a', 'd', weight=0.3)
  
  G2 = nx.Graph()
  G2.add_edge('a', 'b', weight=0.9)
  G2.add_edge('a', 'f', weight=0.5)
  G2.add_edge('c', 'd', weight=0.1)
  G2.add_edge('c', 'e', weight=0.4)
  G2.add_edge('c', 'f', weight=0.2)
  G2.add_edge('a', 'd', weight=0.1)
  
  edges = G.edges()
  weights = [G[u][v]['weight'] for u,v in edges] # liste des poids des edges
  
  fig = plt.figure(figsize=(8, 8))
  m = Basemap(projection='npstere',boundinglat=48,lon_0=270,resolution='l')
  m.etopo(scale=0.5, alpha=0.5)
  mx1,my1=m(-6.266155,53.350140) #would be long, lat coordinates of city 1
  mx2,my2=m(-21.827774, 64.128288) #would be long, lat coordinates of city 2
  
  nx.draw_networkx(G1,center=(mx1,my1),pos=nx.spring_layout(G1),node_size=200,node_color='green')
  nx.draw_networkx(G2,center=(mx2,my2),pos=nx.spring_layout(G2),node_size=200,node_color='red')
  plt.title("North Polar Stereographic Projection")
  plt.show()
  

- sol

Answer 1

通过单独计算节点的位置，我可以很好地绘制网络图。你可以尝试使用此片段代码替换你的相关部分并再次尝试。

# (other code above this line)
#
import numpy as np
# compute the positions here
# proper scaling (500000) is applied to the original positions ..
# .. obtained from xxx_layout() to get good spreading
pos1 = nx.spring_layout(G1)
for ea in pos1.keys():
    pos1[ea] =  np.array([mx1, my1]) + pos1[ea]*500000

pos2 = nx.circular_layout(G2)
for ea in pos2.keys():
    pos2[ea] =  np.array([mx2, my2]) + pos2[ea]*500000

nx.draw_networkx(G1, pos=pos1, node_size=100, node_color='green')
nx.draw_networkx(G2, pos=pos2, node_size=100, node_color='red')
#
# (more code below this line)

输出的图表： 编辑 备选版本：

import numpy as np
# compute the positions here
# proper scaling (500000) is applied to the original positions ..
# .. obtained from xxx_layout() to get good spreading

pos1 = nx.spring_layout(G1, scale=500000, center=[mx1, my1])
pos2 = nx.circular_layout(G2, scale=500000, center=[mx2, my2])

nx.draw_networkx(G1, pos=pos1, node_size=100, node_color='green')
nx.draw_networkx(G2, pos=pos2, node_size=100, node_color='red')
#
# (more code below this line)

- swatchai

---

不错的提议，我会尝试解决。我必须定义最佳矩形的大小，以绘制两个位置之间的每个子图。谢谢。 - sol