Draw a graph from networkx centered on a basemap position

Question

I'm searching to plot multiple sub-graphes on a map, each sub-graph would be centered in one geographical position (or one coordinate of a plot). Nodes don't have position by themselves (or they all belong to a city), but each subgraph corresponds to a local situation.

• 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://stackoverflow.com/a/29597209/839119 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()

Answer 1

By computing nodes' location separately, I can plot the networks quite nicely. You can try again using this snippet code in place of the relevant parts in yours.

# (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)

The output plot:

Edit

Alternate version:

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)