from gamemanager import GameManager from gp.criteria import * from pyevolve import Util from pyevolve import GTree from pyevolve import GSimpleGA from pyevolve import Consts from pyevolve import Selectors import pyevolve error_accum = Util.ErrorAccumulator() NUM_MATCHES = 3.0 class TrainingContext(): def __init__(self, fitness_func): class ThinkTime: def get(self): return 0.01 self.thinkTime = ThinkTime() self.manager = GameManager(root=None, parent=self, training=True, fitness=fitness_func) def eval_func(chromosome): global error_accum error_accum.reset()
from pyevolve import Util from pyevolve import GTree from pyevolve import GSimpleGA from pyevolve import Consts import math rmse_accum = Util.ErrorAccumulator() def gp_add(a, b): return a + b def gp_sub(a, b): return a - b def gp_mul(a, b): return a * b def gp_sqrt(a): return math.sqrt(abs(a)) def eval_func(chromosome): global rmse_accum rmse_accum.reset() code_comp = chromosome.getCompiledCode() for a in xrange(0, 5):