pairwiseStability_Example.py

'''
@author Michael J Bommarito II
@date Mar 4, 2010
'''

import igraph
from pairwiseStability import *

'''
Create G, the list of graphs over time.
'''
G = []
G.append(igraph.Graph([(0,1),(1,2),(2,3)], directed = True))
G.append(igraph.Graph([(0,1),(1,2),(2,3),(4,3),(5,3),(5,4)], directed = True))
G.append(igraph.Graph([(0,1),(1,2),(2,3),(4,3),(5,3),(5,4), (6,0), (6,1), (2,0)], directed = True))
G.append(igraph.Graph([(0,1),(1,2),(2,3),(4,3),(5,3),(5,4), (2,0), (7,5), (7,4), (7,3), (7,6), (6,5), (6,4), (6,3)], directed = True))

'''
Because we want to support graphs with VERTEX REMOVAL,
we need to explicitly label each vertex.  This could be
a string or a number, so long as it is unique!  In this
case, no removal occurs and so the vertex index is used
as the label.
'''
for g in G:
	for i,v in enumerate(g.vs):
		v['label'] = i

'''
This calculates the corresponding stabilities.
'''
print 'Edge Betweenness: ', pairwiseStability_Betweenness(G)
print 'Fast Greedy: ', pairwiseStability_FastGreedy(G)
print 'Label Propagation: ', pairwiseStability_LabelPropagation(G)
print 'Leading Eigenvector: ', pairwiseStability_Eigenvector(G)
print 'Walktrap: ', pairwiseStability_Walktrap(G)

'''
Here are the results:
Edge Betweenness:  0.430555555556
Fast Greedy:  0.6
Label Propagation:  0.466666666667
Leading Eigenvector:  0.6
Walktrap:  0.6
'''