/usr/share/doc/python-pyevolve-doc/examples/pyevolve_ex8_gauss_int.py is in python-pyevolve-doc 0.6~rc1+svn398+dfsg-7.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | from pyevolve import G1DList
from pyevolve import GSimpleGA
from pyevolve import Selectors
from pyevolve import Mutators
# This function is the evaluation function, we want
# to give high score to more zero'ed chromosomes
def eval_func(chromosome):
score = 0.0
# iterate over the chromosome
for value in chromosome:
if value==0:
score += 0.1
return score
def run_main():
# Genome instance
genome = G1DList.G1DList(40)
# The gauss_mu and gauss_sigma is used to the Gaussian Mutator, but
# if you don't specify, the mutator will use the defaults
genome.setParams(rangemin=0, rangemax=10, gauss_mu=4, gauss_sigma=6)
genome.mutator.set(Mutators.G1DListMutatorIntegerGaussian)
# The evaluator function (objective function)
genome.evaluator.set(eval_func)
# Genetic Algorithm Instance
ga = GSimpleGA.GSimpleGA(genome)
#ga.selector.set(Selectors.GRouletteWheel)
ga.setGenerations(800)
# Do the evolution, with stats dump
# frequency of 10 generations
ga.evolve(freq_stats=150)
# Best individual
print ga.bestIndividual()
if __name__ == "__main__":
run_main()
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