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#===============================================================================
# Pyevolve version of the Infinite Monkey Theorem
# See: http://en.wikipedia.org/wiki/Infinite_monkey_theorem
# By Jelle Feringa
#===============================================================================
from pyevolve import G1DList
from pyevolve import GSimpleGA, Consts
from pyevolve import Selectors
from pyevolve import Initializators, Mutators, Crossovers
import math
sentence = """
'Just living is not enough,' said the butterfly,
'one must have sunshine, freedom, and a little flower.'
"""
numeric_sentence = map(ord, sentence)
def evolve_callback(ga_engine):
generation = ga_engine.getCurrentGeneration()
if generation%50==0:
indiv = ga_engine.bestIndividual()
print ''.join(map(chr,indiv))
return False
def run_main():
genome = G1DList.G1DList(len(sentence))
genome.setParams(rangemin=min(numeric_sentence),
rangemax=max(numeric_sentence),
bestrawscore=0.00,
gauss_mu=1, gauss_sigma=4)
genome.initializator.set(Initializators.G1DListInitializatorInteger)
genome.mutator.set(Mutators.G1DListMutatorIntegerGaussian)
genome.evaluator.set(lambda genome: sum(
[abs(a-b) for a, b in zip(genome, numeric_sentence)]
))
ga = GSimpleGA.GSimpleGA(genome)
#ga.stepCallback.set(evolve_callback)
ga.setMinimax(Consts.minimaxType["minimize"])
ga.terminationCriteria.set(GSimpleGA.RawScoreCriteria)
ga.setPopulationSize(60)
ga.setMutationRate(0.02)
ga.setCrossoverRate(0.9)
ga.setGenerations(5000)
ga.evolve(freq_stats=100)
best = ga.bestIndividual()
print "Best individual score: %.2f" % (best.score,)
print ''.join(map(chr, best))
if __name__ == "__main__":
run_main()
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