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TermNSI/Projets/src/_combinaison.py
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from individual_interface import *
from random import *
from math import *
CHIFFRE = ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]
class Combinaison(Individual_Interface):
def copy(self):
'''
build a copy of self, the genome is a copy of self's genome
:return: a new Individual which is a "clone" of self
:rtype: an Individual object
'''
copy = Combinaison(self.get_size())
copy.set_value(self.get_value())
return copy
def init_value(self):
'''
randomly initialize the genome value of self
'''
return [choice(CHIFFRE) for _ in range (self.get_size())]
def cross_with(self, other):
'''
perform a 1 point crossover between self and other, two new built individuals are returned
:param other: the individual to cross with
:type other: an Individual object
:return: the two new Individuals built by 1 point crossover operation
:rtype: 2-uple of individuals
'''
value = self.get_value()
other_value = other.get_value()
pivot = randint (0, self.get_size())
test_1, test_2 = Combinaison(self.get_size()), Combinaison(self.get_size())
test_1.set_value(value[:pivot] + other_value[pivot:])
test_2.set_value(other_value[:pivot] + value[pivot:])
return (test_1, test_2)
def mutate(self, probability):
'''
apply mutation operation to self : each element of the genome sequence is randomly changed with given probabiliy
side effect : self's genome is modified
:param probability: the probability of mutation for every gene
:type probability: float
:UC: probability in [0,1[
'''
for gene in range(len(self.get_value())):
proba = uniform(0, 1)
if proba < probability :
self.mutate_gene(gene)
def mutate_gene(self, gene):
temp = self.get_value()
self.set_value(temp[:gene] + [choice(CHIFFRE)] + temp [gene+1:])