def breed():
alive_number = Constants.POPULATION_SIZE - Constants.KILL_SIZE
sorted_individuals = [i['parameters'] for i in Database.get_all_individuals_sorted()[:alive_number]]
for i in range(Constants.KILL_SIZE):
pick1, pick2 = random.sample(sorted_individuals, 2)
parameters = genetic.combine_and_mutate(pick1, pick2)
Database.add_individual_to_current_generation(parameters)
def index():
# Check table, populate if empty
# Show two random individuals in the current gen
populate_current_generation_if_empty()
a, b = Database.get_random_individuals(2)
ar = render_individual(a['parameters'])
br = render_individual(b['parameters'])
aid, bid = a['id'], b['id']
prg = str(float(Database.num_comparisons()) / Constants.COMPARISONS_PER_GENERATION * 100)
gen = len(Database.get_historical_individuals())
magic_color = Database.get_all_individuals_sorted()[0]['parameters']['palette_1']
magic_color = '#%06x' % magic_color
return render_template('index.html', left_id=aid, left=ar, right_id=bid, right=br, progress=prg, generation=gen, magic_color=magic_color)
def reset_scores():
for individual in Database.get_all_individuals_sorted():
Database.update_elo_for_id(individual["id"],1000.0)
def kill_unfit():
sorted_individuals = Database.get_all_individuals_sorted()
unfit = sorted_individuals[-Constants.KILL_SIZE:]
Database.delete_individuals(unfit)
def save_best_to_history():
sorted_individuals = Database.get_all_individuals_sorted()
Database.add_historical_individual(sorted_individuals[0])
