view ch5ex6-3.py @ 36:305cc03c2750

Chapter 5.5, exercise 6, #3: compute WS clustering coefficient and characteristic length on a BA model graph.
author Brian Neal <bgneal@gmail.com>
date Thu, 10 Jan 2013 19:24:02 -0600
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"""Chapter 5.5, exercise 6 in Allen Downey's Think Complexity book.

3. Use the BA model to generate a graph with about 1000 vertices and compute the
   characteristic length and clustering coefficient as defined in the Watts and
   Strogatz paper. Do scale-free networks have the characteristics of
   a small-world graph?

"""

from ch5ex6 import BAGraph

g = BAGraph(5, 5)

for i in xrange(1000):
    g.step()

g.set_edge_length(1)
print "Clustering coefficient:", g.clustering_coefficient()
print "Characteristic length:", g.big_l3()