Mercurial > public > think_complexity
view ch5ex6-3.py @ 48:98eb01502cf5 tip
Follow up to last commit. Re-orient the r-pentomino. Added progress display.
author | Brian Neal <bgneal@gmail.com> |
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date | Wed, 31 Jul 2013 20:37:12 -0500 |
parents | 305cc03c2750 |
children |
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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()