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# ランダムなグラフの作成

import networkx as nx

import matplotlib.pyplot as plt

G = nx.random_geometric_graph(200, 0.125)
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
p = nx.single_source_shortest_path_length(G, ncenter)

fig = plt.figure(figsize=(8,8))
nx.draw_networkx_edges(G, pos, nodelist=[ncenter],alpha=0.4)
nx.draw_networkx_nodes(G, pos, node_size=40)
plt.xlim(-0.05,1.05)
plt.ylim(-0.05,1.05)
plt.axis('off')
plt.show()

# ある頂点からKステップの頂点を求める

K = 5

nodedict = {}
for k in range(1, K + 1):
Nk = nx.single_source_shortest_path_length(G, ncenter, cutoff=k)
Nk = [n for (n, v) in Nk.items() if v == k]
nodedict[k] = Nk

# 可視化してみる

fig = plt.figure(figsize=(8,8))

nx.draw_networkx_edges(G, pos, nodelist=[ncenter], alpha=0.4)
nx.draw_networkx_nodes(G, pos, node_size=40, node_color='black')
nx.draw_networkx_nodes(G, pos, node_size=50, node_color='red', nodelist=nodedict[1])
nx.draw_networkx_nodes(G, pos, node_size=50, node_color='green', nodelist=nodedict[2])
nx.draw_networkx_nodes(G, pos, node_size=50, node_color='cyan', nodelist=nodedict[3])
nx.draw_networkx_nodes(G, pos, node_size=50, node_color='blue', nodelist=nodedict[4])
nx.draw_networkx_nodes(G, pos, node_size=50, node_color='magenta', nodelist=nodedict[5])
plt.xlim(-0.05,1.05)
plt.ylim(-0.05,1.05)
plt.axis('off')
plt.show()