Random weighted graphs.py

# Code for generating random weighted graphs in networkX and printing off the edges

import networkx as nx
import matplotlib.pyplot as plt

from random import *

# Create a random graph with 10 nodes and a 50% chance of connection. 
# Change the 10 and 0.5 for graphs with more/fewer nodes and more/fewer connections.
G = nx.random_graphs.gnp_random_graph(10,.5)

m = G.number_of_edges()

# Assign random weights between 1 and 5 to each edge. 
# Change the 1 and 5 for a different range. 
weights = [randint(1,5) for r in range(m)]

unweighted_edges = list(G.edges())
weighted_edges = [(unweighted_edges[i][0], unweighted_edges[i][1], {'weight':weights[i]}) for i in range(m)]
newG = nx.Graph(weighted_edges)

# Drawing the graph
pos = nx.circular_layout(newG)
# pos = nx.spring_layout(newG)
nx.draw(newG,pos, with_labels=True, node_color = "cyan")   # Added the with_labels = True to show vertex labels
labels = nx.get_edge_attributes(newG, 'weight')
nx.draw_networkx_edge_labels(G,pos,edge_labels=labels)
plt.show()

# Finally, print off the edge list with the weights. 
print(newG.edges(data=True))