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
