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algorithme génétique
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| import operator | |
| import random | |
| def computePerfPopulation(population, password): | |
| populationPerf = {} | |
| for individual in population: | |
| populationPerf[individual] = fitness(password, individual) | |
| return sorted(populationPerf.items(), key = operator.itemgetter(1), reverse=True) | |
| def selectFromPopulation(populationSorted, best_sample, lucky_few): | |
| nextGeneration = [] | |
| for i in range(best_sample): | |
| nextGeneration.append(populationSorted[i][0]) | |
| for i in range(lucky_few): | |
| nextGeneration.append(random.choice(populationSorted)[0]) | |
| random.shuffle(nextGeneration) | |
| return nextGeneration |
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