song.crossover_chance = get_crossover_prob(song.score, total_score)
song.mutation_chance = get_mutation_prob(song.crossover_chance)
else:
with open(save_file, 'w+') as save:
for song in song_list:
save.write(str(song) + '\n')
raise SystemExit
song_list = BiasedRandomSequence(*song_list, insert_key=lambda v: v.crossover_chance)
new_song_list = []
for i in range(len(song_list)):
song1, song2 = sample_pair(song_list)
song3 = song1.crossover(song2, random_crossover_point(chromo_len, randomizer))
if song2.mutation_chance <= get_prob(randomizer):
delta_mask = random_delta_mask(max_step_size, randomizer, song3)
song3.mutate(*delta_mask)
new_song_list.append(song3)
song_list = new_song_list
get_population_sample(config_file, *pheno_list)
logging.info("avg fitness: {}, max fitness: {}, min fitness: {}".format(get_avg(*score_list), max(score_list), min(score_list)))
gen_num = get_gen_num(pheno_list[1], config_file)
value_list = [get_avg(*score_list), max(score_list), min(score_list), get_avg(*diversity_list)]
append_to_graph_file(config_file.graph_file, gen_num, *value_list)
#pre-crossover setup
new_pheno_list = []
top_pheno = find_min_pheno(pheno_list, config_file)
new_pheno_list.append(top_pheno)
pheno_list = BiasedRandomSequence(*pheno_list, insert_key=lambda v: v.crossover_chance)
#crossover/mutation loop
for i in range(get_pheno_count(config_file) - 1):
#phenotype selection and crossover
pheno1, pheno2 = sample_pair(pheno_list)
c_over_point = randomizer.get_crossover_point(pheno1, pheno2)
pheno3 = pheno1.crossover(pheno2, c_over_point)
log_cross_over(pheno1, pheno2, c_over_point)
#mutation phase
if randomizer.get_prob() <= config_file.mutation_chance:
if randomizer.get_prob() <= config_file.chromo_delete_prob and len(pheno3) > 1:
pheno3 = delete_mutation(pheno3, randomizer)
log_delete_mutation(pheno3)
elif randomizer.get_prob() <= config_file.chromo_add_prob:
pheno3 = add_mutation(pheno3, config_file)
log_add_mutation(pheno3)
else:
pheno3 = mutation(pheno3, config_file)
log_mutation(pheno3)
