python - Networkx 随机几何图限制节点在半径 r 内

Question

所以我有来自 networkx 示例的这段代码，但我试图弄清楚如何将节点限制在半径“r”内，以便在圆的边界内绘制随机几何图形。我知道我会如何在逻辑上做到这一点，但我对一切的运作方式有点困惑，并且一直在尝试自己解决问题，但到目前为止还没有解决方案。感谢您的帮助!

import networkx as nx
import matplotlib.pyplot as plt

G = nx.random_geometric_graph(1000,0.1)

# position is stored as node attribute data for random_geometric_graph
pos = nx.get_node_attributes(G,'pos')

# find node near center (0.5,0.5)
dmin =1
ncenter =0
for n in pos:
    x,y = pos[n]
    d = (x-0.5)**2+(y-0.5)**2
    if d<dmin:
        ncenter = n
        dmin = d

# color by path length from node near center
p = nx.single_source_shortest_path_length(G,ncenter)

plt.figure(figsize=(8,8))
#node_color=p.values()
nx.draw_networkx_edges(G,pos,nodelist=[ncenter],alpha=0.4)
nx.draw_networkx_nodes(G,pos,nodelist=p.keys(),
                   node_size=80,
                   node_color='#0F1C95',
                   cmap=plt.cm.Reds_r)

plt.xlim(-0.05,1.05)
plt.ylim(-0.05,1.05)
plt.axis('off')
plt.savefig('random_geometric_graph.png')
plt.show()

Answer 1

你可以使用像这样的字典理解

p = {node:length for node, length in nx.single_source_shortest_path_length(G,ncenter).items()
     if length < 5}

将 dict 限制为与 ncenter 的距离为 < 5 的那些节点。

对于 Python2.6 或更早的版本，你可以使用

p = dict((node, length) for node, length in nx.single_source_shortest_path_length(G,ncenter).items()
     if length < 5)

---

你也可以替换

dmin =1
ncenter =0
for n in pos:
    x,y = pos[n]
    d = (x-0.5)**2+(y-0.5)**2
    if d<dmin:
        ncenter = n
        dmin = d

用单线:

ncenter, _ = min(pos.items(), key = lambda (node, (x,y)): (x-0.5)**2+(y-0.5)**2)

---

要仅绘制与 ncenter 的距离为 < 5 的那些节点，请定义子图:

H = G.subgraph(p.keys())    
nx.draw_networkx_edges(H, pos, alpha = 0.4)
nx.draw_networkx_nodes(H, pos, node_size = 80, node_color = node_color,
                       cmap = plt.get_cmap('Reds_r'))

---

import networkx as nx
import matplotlib.pyplot as plt
G = nx.random_geometric_graph(1000, 0.1)

# position is stored as node attribute data for random_geometric_graph
pos = nx.get_node_attributes(G, 'pos')

# find node near center (0.5,0.5)
ncenter, _ = min(pos.items(), key = lambda (node, (x, y)): (x-0.5)**2+(y-0.5)**2)

# color by path length from node near center
p = {node:length
     for node, length in nx.single_source_shortest_path_length(G, ncenter).items()
     if length < 5}

plt.figure(figsize = (8, 8))
node_color = p.values()
H = G.subgraph(p.keys())    
nx.draw_networkx_edges(H, pos, alpha = 0.4)
nx.draw_networkx_nodes(H, pos, node_size = 80, node_color = node_color,
                       cmap = plt.get_cmap('Reds_r'))

plt.xlim(-0.05, 1.05)
plt.ylim(-0.05, 1.05)
plt.axis('off')
plt.savefig('random_geometric_graph.png')
plt.show()