Xfoil & Python: optimization of airfoil by genetic algorithm :)

This is very simle implementation made in one weekend of learning python and Xfoil simultaneously - so don't expect anything clever or effective

genom is represented by Lower and Upper radius of leading edge, and thickness and camber in 25%, 50%, and 70% of chord. Thus 8 dimensions
These points are then interpolated by bezier curve and exported to Xfoil which compute maximal Lift-to-drag ratio for given xfoil.

My script in python than select 10 best from each generation, and replaces other by some mutations of these best. Mutations are:
1) generate new from scratch randomly
2) weakly modify some of best radndomly
3) Interpolate 2 of the best
4) Crossover - choose randomly each gen from either mother or father from random 2 best

Enjoy
(Actually for thi problem, and in this implementation it isn't much better than Monte Carlo with just one agent )

----------- the source code -----------

If anybody is interested. But I warn you:its not very sophisticated. It was rather a test of interfacing Xfoil to python. The "genetic algorithm" is not clever and well tuned at all. ( and I didn't tuch since 2011 )

hope the google-drive link would work fine:
https://drive.google.com/file/d/0B4W6nulE1YeTNUdSREhHVmdhc3c/edit?usp=sharing

you have to download xfoil ( I tested with Xfoil6.96 )
http://web.mit.edu/drela/Public/web/xfoil/
and you should set "XFOILPATH" in "xfoil_dat.py"