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- import networkx as nx
- import matplotlib.pyplot as plt
- import itertools
-
- def EgocentricNetwork(G,v):
-
- egocentric_network_edge_list = []
- egocentric_network_node_list = [v]
- for i in G.neighbors(v):
- egocentric_network_node_list.append(i)
- egocentric_network_edge_list.append((v,i))
- egocentric_network_node_list.sort()
- egocentric_network_edge_list = list(tuple(sorted(p)) for p in egocentric_network_edge_list)
- for i in list(itertools.combinations(egocentric_network_node_list, 2)): #generates all possible pairs of nodes
- if i in G.edges() and i not in egocentric_network_edge_list:
- egocentric_network_edge_list.append(i)
-
- temp = []
- temp.extend(egocentric_network_node_list)
- for i in temp:#print i," ",G.neighbors(i)
- for j in G.neighbors(i):
- if j not in egocentric_network_node_list:
- egocentric_network_node_list.append(j)
- if (j,i) in G.edges() and (j,i) not in egocentric_network_edge_list:
- egocentric_network_edge_list.append((j,i))
- elif (i,j) in G.edges() and (i,j) not in egocentric_network_edge_list:
- egocentric_network_edge_list.append((i,j))
-
- return egocentric_network_edge_list,egocentric_network_node_list
- #takes input from the file and creates a graph
- def CreateGraph():
- G = nx.Graph()
- f = open('input.txt')
- n = int(f.readline())
- for i in range(n):
- G.add_node(i+1)
- no_of_edges = int(f.readline())
- for i in range(no_of_edges):
- graph_edge_list = f.readline().split()
- G.add_edge(int(graph_edge_list[0]), int(graph_edge_list[1]))
- vert = int(f.readline())
- return G, vert
- #draws the graph and displays the weights on the edges
- def DrawGraph(G,egocentric_network_edge_list,egocentric_network_node_list):
- pos = nx.spring_layout(G)
- nx.draw(G, pos, with_labels = True, node_color = 'blue', alpha = 0.2) #with_labels=true is to show the node number in the output graph
- nx.draw_networkx_edges(G, pos, edgelist = egocentric_network_edge_list , width = 2.5, alpha = 0.8, edge_color = 'blue')
- nx.draw_networkx_nodes(G,pos, nodelist = egocentric_network_node_list, node_color = 'blue', alpha = 0.5)
- return pos
- def DrawGraph(G, egocentric_network_edge_list, egocentric_network_node_list, vert):
- pos = nx.spring_layout(G)
- nx.draw(G, pos, with_labels = True, node_color = 'blue', alpha = 0.8) #with_labels=true is to show the node number in the output graph
- nx.draw_networkx_edges(G, pos, edgelist = egocentric_network_edge_list , width = 2.5, alpha = 0.8, edge_color = 'red')
- nx.draw_networkx_nodes(G,pos, nodelist = egocentric_network_node_list, node_color = 'red', alpha = 0.5)
- nx.draw_networkx_nodes(G,pos,nodelist=[vert],node_color='green',node_size=500,alpha=0.8)
- return pos
- def CentralityMeasures(G):
- # Betweenness centrality
- bet_cen = nx.betweenness_centrality(G)
- # Closeness centrality
- clo_cen = nx.closeness_centrality(G)
- # Eigenvector centrality
- eig_cen = nx.eigenvector_centrality(G)
- # Degree centrality
- deg_cen = nx.degree_centrality(G)
- #print bet_cen, clo_cen, eig_cen
-
- #main function
- if __name__== "__main__":
- G,vert = CreateGraph()
- egocentric_network_edge_list,egocentric_network_node_list = EgocentricNetwork(G,vert)
- DrawGraph(G,egocentric_network_edge_list,egocentric_network_node_list, vert)
- CentralityMeasures(G)
- plt.show()
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