运行进化算法实验的工具
natural-selection的Python项目详细描述
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by Zipfian Science
由Zipfian Science创建和运行进化算法（EA）实验的Python工具。在
有关文档，请参阅docs。在
源位于GitHub。在
安装
^{pr2}$和使用
importrandomfromnatural_selection.gaimportGene,Genome,Individual,Island# Create a geneg_1=Gene(name="test_int",value=3,gene_max=10,gene_min=1,rand_type_func=random.randint)g_2=Gene(name="test_real",value=0.5,gene_max=1.0,gene_min=0.1,rand_type_func=random.random)# Add a list of genes to a genomegen=Genome([g_1,g_2])# Next, create an individual to carry these genes and evaluate themfitness_function=lambdagen,x,y:gen[0].value*x+yadam=Individual(fitness_function,name="Adam",genome=gen)# Now we can create an island for running the evolutionary process# Notice the fitness function parameters are given here.params=dict()params['x']=0.5params['y']=0.2isolated_island=Island(function_params=params)# Using a single individual, we can create a new populationisolated_island.create(adam,population_size=5)# And finally, we let the randomness of life do its thing: optimisebest_individual=isolated_island.evolve_generational(n_generations=5)# After running for a few generations, we have an individual with the highest fitnessfitness=best_individual.fitnessgenes=best_individual.genomeforgeneingenes:print(gene.name,gene.value)
释放
- 日期：2020-12-07
- 版本：0.1.1
- 项目
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