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):
