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annotate ch5ex6-3.py @ 42:039249efe42f
Chapter 6, exercise 2, #4. Wrote a program to output the center column of
a rule 30 CA as a stream of bytes. It is very slow though. It has to run a very
long time to produce enough data for dieharder. Committing it now but will have
to let it run overnight or something to generate a large file.
| author | Brian Neal <bgneal@gmail.com> |
|---|---|
| date | Sun, 13 Jan 2013 16:24:00 -0600 |
| parents | 305cc03c2750 |
| children |
| rev | line source |
|---|---|
| bgneal@36 | 1 """Chapter 5.5, exercise 6 in Allen Downey's Think Complexity book. |
| bgneal@36 | 2 |
| bgneal@36 | 3 3. Use the BA model to generate a graph with about 1000 vertices and compute the |
| bgneal@36 | 4 characteristic length and clustering coefficient as defined in the Watts and |
| bgneal@36 | 5 Strogatz paper. Do scale-free networks have the characteristics of |
| bgneal@36 | 6 a small-world graph? |
| bgneal@36 | 7 |
| bgneal@36 | 8 """ |
| bgneal@36 | 9 |
| bgneal@36 | 10 from ch5ex6 import BAGraph |
| bgneal@36 | 11 |
| bgneal@36 | 12 g = BAGraph(5, 5) |
| bgneal@36 | 13 |
| bgneal@36 | 14 for i in xrange(1000): |
| bgneal@36 | 15 g.step() |
| bgneal@36 | 16 |
| bgneal@36 | 17 g.set_edge_length(1) |
| bgneal@36 | 18 print "Clustering coefficient:", g.clustering_coefficient() |
| bgneal@36 | 19 print "Characteristic length:", g.big_l3() |