import ribosome import random as rd Generation_Num = int(input("Input Generation Number")) gene_list = [] for i in range(Generation_Num): gene_list = Genetic.Read_Gene() if (len(gene_list) == 0): import startup gene_score_list = [] selected_gene = [] descendants_gene = [] descendant_mutated = [] score_list = [] network_list = ribosome.Translate_Into_Networks(4, [1, 4], 2, -1) score_list = SNN.return_score(network_list, i) gene_score_list.append(score_list) selected_gene: list = NEAT.calc_and_select_gene(gene_score_list, gene_list) gene_num: int = int(len(gene_list) / 2) for k in range(gene_num): cross1 = rd.choice(selected_gene) cross2 = rd.choice(selected_gene) print(cross1, cross2) Agene1, Agene2 = NEAT.Crossover(cross1, cross2) descendants_gene.append(Agene1) descendants_gene.append(Agene2) for idx_gene, gene in enumerate(descendants_gene): descendant_mutated.append( NEAT.Mutate(gene, score_list[idx_gene], 1000000)) Genetic.Write_Gene(descendants_gene)
import Genetic Gene_Pool = Genetic.Generate_Gene_Pool(8, 15) Genetic.Write_Gene(Gene_Pool) import ribosome