печать победившего человека из генетического алгоритма?

Question

Я просматриваю этот код, который я нашел, и я не могу разобраться, как печатать победившего человека. По существу, я пытаюсь создать генетический алгоритм, который будет генерировать индивидуум из N чисел, суммируемых на общую сумму X. Этот вопрос был рассмотрен на Lethian: http://lethain.com/genetic-algorithms-cool-name-damn-simple/ Но я не могу понять, как напечатать человека, который является результатом эволюции.

Heres пример кода:

from random import randint, random 
    from operator import add 
    target = 5 #this defines the target number we are trying to reach 
    p_count = 100 #this defines the number of individuals available to          mutate for the desired result 
    i_length = 6 #this defines the length of each individual, the number of intergers in it 
    i_min = 0 #this defines the minimum value of an integer in the individual 
    i_max = 100 #this defines the maximum value of an integer in the individual 
    def individual(length, min, max): 
     return [ randint(min,max) for x in xrange(length) ] #Creates an individual. Defines an individual by the number of numbers contained in it and their min/max 
    def population(count, length, min, max): 
     return [ individual(length, min, max) for x in xrange(count) ] #Creates population from individuals. This sets the number of individuals in the population (count), the number of numbers in each individual (length), and the min and max numbers for the individual   
    def fitness(individual, target): 
     sum = reduce(add, individual, 0) 
     return abs(target-sum) #determines the fitness. does this by adding the indivduals numbers together, and taking that value from the target value 
    def grade(pop, target): 
     summed = reduce(add, (fitness(x, target) for x in pop)) 
     return summed/(len(pop) * 1.0) #This returns an average fitness to compare populations to. 
    def evolve(pop, target, retain=0.2, random_select=0.05, mutate=0.01): #This evolves a population, retaining 20%, randomly selecting 5% so it doesnt get stuck/lose variance, and mutates 1%. 
     graded = [ (fitness(x, target), x) for x in pop] 
     graded = [ x[1] for x in sorted(graded)] 
     retain_length = int(len(graded)*retain) 
     parents = graded[:retain_length] 
     for individual in graded[retain_length:]: 
      if random_select > random(): 
       parents.append(individual) 
     for individual in parents: 
      if mutate > random(): 
       pos_to_mutate = randint(0, len(individual)-1) 
       individual[pos_to_mutate] = randint(
        min(individual), max(individual)) 
     parents_length = len(parents) 
     desired_length = len(pop) - parents_length 
     children = [] 
     while len(children) < desired_length: 
      male = randint(0, parents_length-1) 
      female = randint(0, parents_length-1) 
      if male != female: 
       male = parents[male] 
       female = parents[female] 
       half = int(len(male)/2) 
       child = male[:half] + female[half:] 
       children.append(child) 
     parents.extend(children) 
     return parents 

Любая помощь будет высоко ценится!

Answer 1

, если я правильно понял U U есть хотите напечатать кандидата решение, которое соответствует критериям УР (как выше частности пригодности) если так вы можете:

def fitness(individual, target): 
    sum = reduce(add, individual, 0) 
    if sum >= target: 
     print individual 
    return abs(target-sum)