class GENEALG:
def __init__(self, play_back=False):
if play_back:
f = open('robot.p', 'rb')
self.parent = pickle.load(f)
f.close()
else:
self.parent = POPULATION(c.popSize)
self.parent.Initialize()
self.parent.Evaluate()
def Evolve(self):
for g in range(c.numGens):
print(g, end=' ')
self.parent.Print()
child = POPULATION(c.popSize)
child.Fill_From(self.parent)
child.Evaluate()
self.parent.ReplaceWith(child)
def Show_Best(self):
bestIndividual = self.parent.Best_Individual()
self.parent.p[bestIndividual].Start_Evaluation(pb=False, pp=True)
self.parent.p[bestIndividual].Compute_Fitness()
print(self.parent.p[bestIndividual].fitness)
def Save(self):
f = open('robot.p', 'wb')
pickle.dump(self.parent, f)
f.close()
import pickle
import constants as c
from population import POPULATION
# import matplotlib.pyplot as plt
parent = POPULATION(c.popSize)
parent.Initialize()
parent.Evaluate(True)
for g in range(c.numGens):
print(g, end=' ')
parent.Print()
child = POPULATION(c.popSize)
child.Fill_From(parent)
child.Evaluate()
parent.ReplaceWith(child)
bestIndividual = parent.Best_Individual()
parent.p[bestIndividual].Start_Evaluation(pb=False, pp=True)
parent.p[bestIndividual].Compute_Fitness()
f = open('robot.p', 'wb')
pickle.dump(parent, f)
f.close()
