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Python Population.saveIndividuals方法代码示例

本文整理汇总了Python中population.Population.saveIndividuals方法的典型用法代码示例。如果您正苦于以下问题:Python Population.saveIndividuals方法的具体用法?Python Population.saveIndividuals怎么用?Python Population.saveIndividuals使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在population.Population的用法示例。


在下文中一共展示了Population.saveIndividuals方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: tournament

# 需要导入模块: from population import Population [as 别名]
# 或者: from population.Population import saveIndividuals [as 别名]
	def tournament(self,population,data,dataEvaluation,heuristicStrategy,attributeCount):
		gladiators = Population(self.gladiator,data,dataEvaluation,False,heuristicStrategy)
		for index in range(self.gladiator):
			chosenOne = random.randint(0,population.size()-1)
			gladiators.saveIndividuals(index,population.getIndividual(chosenOne))
		morpheus = gladiators.getFittest()
		return morpheus
开发者ID:palyfight,项目名称:log635-labo3,代码行数:9,代码来源:geneticalgorithm.py

示例2: nextGeneration

# 需要导入模块: from population import Population [as 别名]
# 或者: from population.Population import saveIndividuals [as 别名]
	def nextGeneration(self,population,data,dataEvaluation,heuristicStrategy,attributeCount):
		nextGen = Population(1+(population.size()*2),data,dataEvaluation,False,heuristicStrategy)
		nextGen.saveIndividuals(0,population.getFittest())
		count = 1
		for index in range(population.size()):
			challenger = self.tournament(population,data,dataEvaluation,heuristicStrategy,attributeCount)
			champion   = self.tournament(population,data,dataEvaluation,heuristicStrategy,attributeCount)
			nextGenChallenger, nextGenChamp = self.crossover(challenger,champion,int(np.floor(challenger.size()/2)),heuristicStrategy)
			nextGen.saveIndividuals(count, nextGenChamp)
			nextGen.saveIndividuals(count+1, nextGenChallenger)
			count += 2

		for index in range(nextGen.size()):
			neo = self.xmen(nextGen.getIndividual(index))
			nextGen.saveIndividuals(index,neo)
		return nextGen
开发者ID:palyfight,项目名称:log635-labo3,代码行数:18,代码来源:geneticalgorithm.py


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