gnp_random_weighted_graph.py

'''
Generates a random weighted graph. 
n = Number of nodes. 
p = Probability of two nodes being connected. Must be between 0 and 1. 
Weights on the edges are randomly generated integers situated between lower_weight and upper_weight. 
Example: random_weighted_graph(6, 0.25, 10, 20) creates a weighted graph with 6 nodes, a 1/4 probability 
of two nodes being connected, and weights on the edges randomly selected between 10 and 20. 
'''

def gnp_random_weighted_graph(n,p,wlow,whigh):
    import random
    G = nx.random_graphs.gnp_random_graph(n,p) 
    m = G.number_of_edges()
    weights = [random.randint(wlow,whigh) for r in range(m)]
    unweighted_edges = G.edges()
    weighted_edges = [(unweighted_edges[i][0], unweighted_edges[i][1], {'weight':weights[i]}) for i in range(m)]
    return nx.Graph(weighted_edges)