naive graph coloring

  Coloring nodes of a graph, simple and naive approach:


Usage is very simple:

python color.py  nbNodes nbEdges dotFileName

and then use dot, neato or twopi for rendering.

Example gallery is here.

don't pay taxes for CO2 emission, just plant more red black trees

Just for fun and making plots like that [small rbtrees gallery].

And here goes the humble code...




:)

python popcnt

popcnt - count bits set ("1") in a integer, of course using python

I've implemented only four ways to do this:

• using look up table 0..255 (no iterations, oen sum and a few shifting by 8 bits)
• naive (number of iterations ==  number of bits)
• Brian Kernighan way (number of iterations == number of bits set)
• pythonic by ugly (count "1"s after calling bin()...)

All function were run on 1000 samples made by 100 random numbers:



And now testing results:

• naive (Zzzzz...)

[Wed, 05 Jun 22:07 E0][cibak@localhost:~/popcnt]> time python testNaive.py
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175.885u 0.055s 2:56.35 99.7%    0+0k 0+0io 0pf+0w

• BK way (much better!)

[Wed, 05 Jun 22:04 E0][cibak@localhost:~/popcnt]> time python testBK.py
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75.853u 0.028s 1:16.03 99.7%    0+0k 0+0io 0pf+0w 

• look up table (niiiice!)

[Wed, 05 Jun 22:06 E0][cibak@localhost:~/popcnt]> time python testLUT.py
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42.828u 0.030s 0:42.93 99.8%    0+0k 0+0io 0pf+0w 

• ugly but pythonic (wut?)

[Wed, 05 Jun 22:04 E1][cibak@localhost:~/popcnt]> time python testUgly.py
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40.880u 0.040s 0:41.06 99.6%    0+0k 0+0io 0pf+0w


And guess what? Ugly (but pythonic) won! Coincidence? I don't think so... ;)

EDIT:
And of course I can completely remove lines with lambda and all this stuff within popcntLUT  and it could be coded just like that:



But it doesn't help to much.

Also one can check say 16 bits look up table, say:



 This should run at least 2 times faster that original popcntLUT.