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']))