随机几何图、自我图、四格图和克拉克哈特中心。

import matplotlib.pyplot as plt
import networkx as nx

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

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

plt.xlim(-0.05, 1.05)
plt.ylim(-0.05, 1.05)
plt.axis('off')
plt.show()
from operator import itemgetter

import matplotlib.pyplot as plt
import networkx as nx

if __name__ == '__main__':
    # Create a BA model graph
    n = 1000
    m = 2
    G = nx.generators.barabasi_albert_graph(n, m)
    # find node with largest degree
    node_and_degree = G.degree()
    (largest_hub, degree) = sorted(node_and_degree, key=itemgetter(1))[-1]
    # Create ego graph of main hub
    hub_ego = nx.ego_graph(G, largest_hub)
    # Draw graph
    pos = nx.spring_layout(hub_ego)
    nx.draw(hub_ego, pos, node_color='b', node_size=50, with_labels=False)
    # Draw ego as large and red
    nx.draw_networkx_nodes(hub_ego, pos, nodelist=[largest_hub], node_size=300, node_color='r')
    plt.show()
import matplotlib.pyplot as plt
import networkx as nx

G = nx.krackhardt_kite_graph()

print("Betweenness")
b = nx.betweenness_centrality(G)
for v in G.nodes():
    print("%0.2d %5.3f" % (v, b[v]))

print("Degree centrality")
d = nx.degree_centrality(G)
for v in G.nodes():
    print("%0.2d %5.3f" % (v, d[v]))

print("Closeness centrality")
c = nx.closeness_centrality(G)
for v in G.nodes():
    print("%0.2d %5.3f" % (v, c[v]))

nx.draw(G)
plt.show()
import matplotlib.pyplot as plt
import networkx as nx

G = nx.grid_2d_graph(4, 4)  # 4x4 grid

pos = nx.spring_layout(G, iterations=100)

plt.subplot(221)
nx.draw(G, pos, font_size=8)

plt.subplot(222)
nx.draw(G, pos, node_color='k', node_size=0, with_labels=False)

plt.subplot(223)
nx.draw(G, pos, node_color='g', node_size=250, with_labels=False, width=6)

plt.subplot(224)
H = G.to_directed()
nx.draw(H, pos, node_color='b', node_size=20, with_labels=False)

plt.show()