1 import matplotlib.pyplot as plt
 2 import networkx as nx
 3
 4 G=nx.binomial_graph(10, 0.3, directed=True) #the graph
 5 G.add_node(10); # add a sole node
 6 layout = nx.spring_layout(G)
 7
 8 plt.figure("source graph")
 9 nx.draw(G, pos=layout, node_color='y')
10
11 plt.figure("eigenCentrality without personalization")
12 pr=nx.eigenvector_centrality(G)
13 print("eigenCentrality without personalization" ,pr)
14 nx.draw(G, pos=layout, node_size=[x * 6000 for x in pr.values()],node_color='m',with_labels=True)
15
16 plt.figure("eigenCentrality with personalization")
17 pr=nx.eigenvector_centrality(G, nstart={0:1, 1:1, 2:10, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1, 9:1, 10:1})
18 print("eigenCentrality with personalization" ,pr)
19 nx.draw(G, pos=layout, node_size=[x * 6000 for x in pr.values()],node_color='m',with_labels=True)
20
21 plt.figure("pageRank without personalization")
22 pr=nx.pagerank(G,alpha=0.85)
23 print("pageRank without personallization", pr)
24 nx.draw(G, pos=layout, node_size=[x * 6000 for x in pr.values()],node_color='m',with_labels=True)
25
26 plt.figure("pageRank with personalization ")
27 pr=nx.pagerank(G,alpha=0.85, personalization={0:1, 1:1, 2:10, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1, 9:1, 10:1})
28 print("pageRank with personalization" , pr)
29 nx.draw(G, pos=layout, node_size=[x * 6000 for x in pr.values()],node_color='m',with_labels=True)
30
31 plt.figure("katzcentrality without personalization")
32 pr=nx.katz_centrality(G, alpha=0.3);
33 print("katzcentrality without personallization ", pr)
34 nx.draw(G, pos=layout, node_size=[x * 6000 for x in pr.values()],node_color='m',with_labels=True)
35
36 plt.figure("katzcentrality with personalization")
37 pr=nx.katz_centrality(G,alpha=0.3, nstart={0:1, 1:1, 2:10, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1, 9:1, 10:1})
38 print("katzcentrality with personalization" , pr)
39 nx.draw(G, pos=layout, node_size=[x * 6000 for x in pr.values()],node_color='m',with_labels=True)
40 plt.show()