class neatHandler:
def __init__(self):
local_dir = os.path.dirname(__file__)
config_path = os.path.join(local_dir, 'config')
self.circuit = Circuit()
self.circuit.start()
self.wireNames = self.circuit.getWires()
self.numInputs = self.circuit.getPathMatrixSize() + len(
self.wireNames) * 4
self.numOutputs = len(self.wireNames) * 4
self.editConfig(config_path)
self.bestFitness = -999999
self.stats = None
self.run(config_path)
def editConfig(self, config_path):
inputSearch = "^num_inputs\s+=\s+(\d)+(\n)?$"
inputReplace = "num_inputs = " + str(
self.numInputs) + "\n"
outputSearch = "^num_outputs\s+=\s+(\d)+(\n)?$"
outputReplace = "num_outputs = " + str(
self.numOutputs) + "\n"
for line in fileinput.input(config_path, inplace=1):
line = re.sub(inputSearch, inputReplace, line)
line = re.sub(outputSearch, outputReplace, line)
sys.stdout.write(line)
print("Config file edited")
def eval_genomes(self, genomes, config):
for genome_id, genome in genomes:
net = neat.nn.FeedForwardNetwork.create(genome, config)
genome.fitness = self.evalNet(net)
if self.bestFitness < genome.fitness:
self.bestFitness = genome.fitness
print("New Best Fitness: " + str(self.circuit.getFitness()))
self.circuit.drawResult()
visualize.plot_stats(self.stats, ylog=False, view=True)
def evalNet(self, net):
self.circuit.restart()
while not (self.circuit.isDone()):
output = net.activate(self.getInputsForCircuit())
if not self.makeMove(output):
break
return self.circuit.getFitness()
def makeMove(self, output):
moves = self.getMoveList(output)
for move in moves:
if move[0](move[2]):
return True
return False
def getMoveList(self, output):
i = 0
moves = []
for wire in self.wireNames:
moves.append((self.circuit.moveNorth, output[i], wire))
i += 1
moves.append((self.circuit.moveEast, output[i], wire))
i += 1
moves.append((self.circuit.moveSouth, output[i], wire))
i += 1
moves.append((self.circuit.moveWest, output[i], wire))
i += 1
moves.sort(key=lambda tup: tup[1])
return moves
def getInputsForCircuit(self):
inputs = []
for row in self.circuit.getPathMatrix():
for i in row:
inputs.append(i)
for wire in self.wireNames:
srow, scol = self.circuit.getWirePosition(wire)
inputs.append(srow / self.circuit.getRows())
inputs.append(scol / self.circuit.getCols())
grow, gcol = self.circuit.getWireGoal(wire)
inputs.append(grow / self.circuit.getRows())
inputs.append(gcol / self.circuit.getCols())
return inputs
def run(self, config_file):
# Load configuration.
config = neat.Config(neat.DefaultGenome, neat.DefaultReproduction,
neat.DefaultSpeciesSet, neat.DefaultStagnation,
config_file)
# Create the population, which is the top-level object for a NEAT run.
p = neat.Population(config)
# Add a stdout reporter to show progress in the terminal.
p.add_reporter(neat.StdOutReporter(True))
self.stats = neat.StatisticsReporter()
p.add_reporter(self.stats)
# Run for up to 300 generations.
winner = p.run(self.eval_genomes, 1000)
self.evalNet(neat.nn.FeedForwardNetwork.create(winner, config))
#os.system("/usr/bin/canberra-gtk-play --id='bell'")
#visualize.draw_net(config, winner, True)
visualize.plot_stats(self.stats, ylog=False, view=True)
#visualize.plot_species(stats, view=True)
print("Turns: " + str(self.circuit.getTotalTurns()))
print("WireLength: " + str(self.circuit.getWireLength()))
print("Completed Wires: " + str(self.circuit.getCompletedWires()))
print("Fitness: " + str(self.circuit.getFitness()))
self.circuit.drawResult()
