myprojects-hg-reborn

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#! /usr/bin/env python
import scipy as s
import networkx as nx






def average_shortest_path_length(G,weighted=False):
# 	    """ Return the average shortest path length.

# 	    Parameters
#     ----------
#     G : NetworkX graph
	
# 	    weighted : bool, optional, default=False
# 	       If true use edge weights on path.  If False,
# 	       use 1 as the edge distance.
	
# 	    Examples
# 	    --------
# 	    >>> G=nx.path_graph(4)
# 	    >>> print nx.average_shortest_path_length(G)
# 	    1.25
	
# 	    """
    if weighted:
        path_length=nx.single_source_dijkstra_path_length
    else:
        path_length=nx.single_source_shortest_path_length
    avg=0.0
    for n in G:
        l=path_length(G,n).values()
        avg+=float(sum(l))/len(l)
    return avg/len(G)    

G=nx.read_edgelist("edgelist-airport")

print "The mean degree is, ", s.mean(G.degree())

print "The mean clustering coeff is, ", s.mean(nx.clustering(G))


print "The length of the graph diameter is, ", nx.diameter(G)

short=average_shortest_path_length(G)

print "the mean shortest path is, ", short

bet_val=nx.betweenness_centrality(G, normalized=False)

#NB: the betweenness is stored as a Python dictionary, now I need to use its .values() method
#to fetch the numerical values of the betweenness of each node

bet_arr=s.asarray(bet_val.values()) #I changed the numerical values of the betweenness for each vertex
#into a numpy array

print "the mean value of the betweenness is, ", bet_arr.mean()/2. #careful about the definitions here!!!
#there is a factor 2 between the (unnormalized) betweenness in networkx and in igraph

#print "bet_arr is, ", bet_arr

print "So far so good"