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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> |
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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()