def __init__(params): debug._remove_fitness_data(params['function_name']) seeding_pool = seeding.pool( params['pool_size'], params['constraint_range'], params['number_of_variables']) params['pool'] = seeding_pool final_pool = _aux(params) print reproduction._build_params(final_pool, 0, params['number_of_variables']) if debug._is_debugging(): debug._chart(params['pool_size'], params['function_name']) return list(final_pool)
def _save_fitnesses(data, number_of_variables, function_name, maximize=True): if _is_debugging(): if maximize == True: best = data[0] else: best = data[-1] f = open('./data/fitness_data{a}.csv'.format(a=function_name), 'a+') decoded_seed = reproduction._build_params(best['seed'], 0, number_of_variables) for a in decoded_seed: print a, best['weight'] f.write("{a},{b}\n".format(a=a, b=best['weight']))