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"""Perform uniform crossovers between the genomes of two organisms.
genome 1 -- A B C D E F G
. . . .
genome 2 -- a b c d e f g
After crossover:
new genome 1 -- a B c d E f G
new genome 2 -- A b C D e F g
Uniform Crossover is a standard crossover technique for
rapid mutation-behavior.
"""
# standard modules
import whrandom
class UniformCrossover:
"""Perform single point crossover between genomes at some defined rates.
This performs a single crossover between two genomes at some
defined frequency. The location of the crossover is chosen randomly
if the crossover meets the probability to occur.
"""
def __init__(self, crossover_prob = .1, uniform_prob = 0.7):
"""Initialize to do uniform crossover at the specified probability and frequency.
"""
self._crossover_prob = crossover_prob
self._uniform_prob = uniform_prob
# a random number generator to test if we have a crossover
self._crossover_rand = whrandom.whrandom()
# a random number generator to pick a crossover location
self._uniform_rand = whrandom.whrandom()
return
def do_crossover(self, org_1, org_2):
"""Potentially do a crossover between the two organisms.
"""
new_org_1 = org_1.copy()
new_org_2 = org_2.copy()
# determine if we have a crossover
crossover_chance = self._crossover_rand.random()
if crossover_chance <= self._crossover_prob:
minlen = min(len(new_org_1.genome),len(new_org_2.genome))
for i in range( minlen ):
uniform_chance = self._uniform_rand.random()
if uniform_chance <= self._uniform_prob:
# cycle element
temp = new_org_1.genome[ i ]
new_org_1.genome[ i ] = new_org_2.genome[ i ]
new_org_2.genome[ i ] = temp
return new_org_1, new_org_2
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