15.六度分隔理论验证

import networkx as nx
import csv
import numpy as np


with open("quakers_nodelist.csv") as nodecsv:
    nodereader = csv.reader(nodecsv)
    nodes = [i for i in nodereader][1:]
    node_names = [n[0] for n in nodes]

with open("quakers_edgelist.csv") as edgecsv:
    edgereader = csv.reader(edgecsv)
    edges = [tuple(e) for e in edgereader][1:]



G = nx.Graph()
G.add_nodes_from(node_names)
G.add_edges_from(edges)



components = nx.connected_components(G)
largest_component = max(components, key=len)
subgraph = G.subgraph(largest_component)


shortest_path_list = []
for i in subgraph.nodes():
    for j in subgraph.nodes():
        if i != j:
            i_j_path = len(nx.shortest_path(subgraph, source=i, target=j)) - 1
            shortest_path_list.append(i_j_path)


average_path_length = np.mean(shortest_path_list)
print(average_path_length)