Watts-Strogatz model for generating small-words random graphs.

WattsStrogatz.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from random import random,choice
import networkx as nx
import matplotlib.pyplot as plt
import time


def watts(G,B):
    aux_edges = G.edges()
    aux_nodes = G.nodes()
    n_edges   = len(aux_edges)
    for i in xrange(n_edges):
	edge = list(aux_edges[i])
	if random()<=B:
	    dest = edge[0]
	    while dest==edge[0]: dest = choice(aux_nodes)
	    edge[1] = dest
	aux_edges[i] = tuple(edge)
    G.clear()
    G.add_edges_from(aux_edges)
    return G
	    
def initialize_graph(N,K,B):
    G = nx.Graph()
    for i in xrange(0,N):
	for j in xrange(0,N): 
	    if abs(i-j)<(K/2): G.add_edge(*(i,j))
    return G
    
def main(N = 5, K = 2, B = 0.5):
    G   = initialize_graph(N,K,B)
    nx.draw(G)
    plt.show()
    watts(G,B)
    nx.draw(G)
    plt.show()

if __name__ == "__main__":
    
    main(N = 1000, K = 5 , B = 0.43)