finding structural properties of a network

asps.py

import networkx as nx
from operator import itemgetter
import sys
import os
import csv
import numpy as np
import math


def build_graph():
    in_file = open(sys.argv[1], 'r')
    G = nx.Graph()

    for row in in_file:
        row = row.split()
        src = int(row[0])
        dest = int(row[1])
        G.add_edge(src, dest)
    return G


def all_asps():
    """
    find ASP to all nodes.
    make the nodes with shortest ASP as sink.
    find packet receival %.
    """
    G = build_graph()
    all_shortest_paths = []
    all_pairs_shortest_paths = nx.all_pairs_dijkstra_path_length(G)
    for node in G.nodes():
        val = sum(all_pairs_shortest_paths[node].values())/len(all_pairs_shortest_paths[node])
        print "ASP to", node, ":", val
    for sink, sink_degree in sorted(G.degree_iter(), key=itemgetter(1), reverse=True)[0:1]:
        print "Sink = ", sink

all_asps()


def all_metrics():
    # input network file
    G = build_graph()
    metrics_file = os.path.splitext(sys.argv[1])[0] + "-metrics.txt"

    for sink, sink_degree in sorted(G.degree_iter(), key=itemgetter(1), reverse=True)[0:1]:
        print "Sink = ", sink

    # eigenvector centrality
    ec = nx.eigenvector_centrality_numpy(G)
    # degree centrality
    dc = nx.degree_centrality(G)
    # betweenness centrality
    bc = nx.betweenness_centrality(G)
    ec_sink = ec[sink]
    dc_sink = dc[sink]
    bc_sink = bc[sink]

    num_nodes = nx.number_of_nodes(G)

    # find adjacency matrix
    adj_mat = nx.adjacency_matrix(G)
    # find eigen values and vectors
    evalues, evectors = np.linalg.eig(adj_mat)
    topological_entropy = math.log(abs(max(evalues)))

    all_shortest_paths_to_sink = []
    all_shortest_paths_to_sink = [nx.dijkstra_path_length(G, node, sink) for node in G.nodes()]

    asp = sum(all_shortest_paths_to_sink)/len(all_shortest_paths_to_sink)
    asp = "%.2f" % asp

    with open(metrics_file, 'w') as f:
        a = csv.writer(f, delimiter='\t')
        data = [ [nx.estrada_index(G),],
                [nx.density(G),],
                [bc_sink,],
                [dc_sink],
                [ec_sink],
                [sum(ec.values()),],
                [sum(dc.values()),],
                [topological_entropy,],
                [asp,]
            ]
        """data = [ ['Estrada Index', nx.estrada_index(G)],
                ['Density', nx.density(G)],
                ['Total Eigenvector centrality', sum(ec.values())],
                ['Total Degree centrality', sum(dc.values())]
            ]"""
        a.writerows(data)