código de algoritmo genético simple en ejemplo de código de Python

Este team especializado pasados algunos días de investigación y de juntar de información, han obtenido los datos necesarios, nuestro deseo es que te sea de gran utilidad en tu plan.

Ejemplo: algoritmo genético python

from random import randint
from random import random

defnewChar():
    r = randint(63,122)if r ==64:
        r =ord(' ')if r ==63:
        r =ord('.')returnchr(r)defmapit(i,m,M, a =0, b =1):return(b - a)*(i - m)/(M-m)classDNA:def__init__(self, num):
        self.num = num
        self.genes =[newChar()for i inrange(num)]
        self.fitnes =0defgetPhrase(self):
        s =''return s.join(self.genes)defcalcFitness(self, target):
        scor =0for idx, gen inenumerate(self.genes):if gen == target[idx]:
                scor +=1
        self.score = scor/len(target)return scor/len(target)defReproduction(self, partner):
        child = DNA(self.num)
        midpoint = randint(0,len(self.genes))for i inrange(self.num):if i < midpoint: 
                child.genes[i]= self.genes[i]else:
                child.genes[i]= partner.genes[i]return child
    
    defmutate(self, mutRate):for i inrange(self.num):
            r = random()if r < mutRate:
                self.genes[i]= newChar()classPapulation:def__init__(self, target, pmax, mutationRate, max_mat_pool =1e5):
        self.target = target
        self.pmax = pmax
        self.mutationRate = mutationRate
        self.papulation =[]for i inrange(pmax):
            self.papulation.append(DNA(len(target)))
        self.matinPool =[]
        self.bestfit =None
        self.max_mat_pool = max_mat_pool
        
    defcalcFitness(self):for i in self.papulation:
            i.calcFitness(self.target)defnaturalSelaction(self):
        maxfit =0for i in self.papulation:if i.score > maxfit:
                maxfit = i.score
                self.bestfit = i
                
        for i in self.papulation:
            n  =int(mapit(i.score,0, maxfit)*100)for j inrange(n):
                self.matinPool.append(i)defdied(self):
        diff =int(len(self.matinPool)- self.max_mat_pool)if diff >0:del self.matinPool[0:diff]defnewGenration(self):for i inrange(self.pmax):
            partnarA = self.matinPool[randint(0,len(self.matinPool)-1)]
            partnarB = self.matinPool[randint(0,len(self.matinPool)-1)]
            child = partnarA.Reproduction(partnarB)
            child.mutate(self.mutationRate)
            self.papulation[i]= child

target ='''Hello world'''

pmax =1000
mutationRate =0.01
genrations =100

k =0
p = Papulation(target,pmax, mutationRate)for i inrange(genrations):
    p.calcFitness()
    p.naturalSelaction()
    p.newGenration()if p.bestfit.getPhrase()== target:
        k+=1#         print('**gen: ', i, p.bestfit.getPhrase())print('gin: ', i,  p.bestfit.getPhrase())
    p.died()

Tienes la posibilidad recomendar esta crónica si lograste el éxito.

---

---

Utiliza Nuestro Buscador