class PhenoType:
def __init__(self, dna):
self.dna = dna
self.network = Network(3, [10, 10, 10], 3)
self.network.import_weights(dna.value)
self.runner = Runner()
self.is_running = False
self.fitness = 0
def tick_neural_network(self):
data = [
self.runner.player.pos.x(),
self.runner.player.pos.y(),
self.runner.distance_next_obstacle()
]
self.network.respond(data)
outputs = [n.output for n in self.network.output_layer]
if not outputs:
return
i = outputs.index(max(outputs))
if i == 0:
return
elif i == 1:
self.runner.player_up()
elif i == 2:
self.runner.player_down()
# @property
# def fitness(self):
# return self.runner.total_ticks_alive
def start(self):
self.is_running = True
self.runner.reset()
def tick(self):
self.runner.tick()
self.tick_neural_network()
self.is_running = not self.runner.stopped
if not self.runner.stopped:
self.fitness += math.floor(
(1.0 - abs(self.runner.player.pos.y()))) * 20
class RunnerDemoWidget(QtWidgets.QWidget):
"""
Runner
"""
def __init__(self):
super(RunnerDemoWidget, self).__init__()
self.setCursor(QtCore.Qt.BlankCursor)
self.setWindowTitle("Runner")
self.tick_timer = QtCore.QTimer()
self.tick_timer.setInterval(10)
self.tick_timer.timeout.connect(self.tick)
self.runner = Runner()
self.runner_painter = RunnerPainter(self.runner, self.rect())
self.network = Network(3, [10, 10, 10], 3)
self.runner_ai = RunnerAI(self.network)
self.runner_ai.on_training_finished = self.training_finished
self.runner_ai.setup()
self.network_painter = NetworkPainter(self.network)
self.network_painter.rect = QRect(0, 0,
self.width() / 2,
self.height() / 2)
self.network.setup()
self.runner_trainer = RunnerTrainer(self.network, self.runner)
self.genetic_algorithm = GeneticAlgorithm()
self.genetic_algorithm.setup()
def training_finished(self):
self.network = self.runner_ai.best_neural_network
def resizeEvent(self, event):
r = QRect(self.width() / 2,
self.height() / 2,
self.width() / 2,
self.height() / 2)
self.runner_painter.rect = r
self.network_painter.rect = QRect(0, 0,
self.width() / 2,
self.height() / 2)
self.update()
def keyPressEvent(self, event):
if event.key() == QtCore.Qt.Key_Enter:
self.network = self.runner_ai.best_neural_network
self.runner.reset()
if event.key() == QtCore.Qt.Key_Space:
fittest_dna = self.genetic_algorithm.get_fittest_dna()
print(fittest_dna.fitness)
self.network.import_weights(fittest_dna.value)
# self.network.setup()
self.runner.reset()
# self.runner_ai.train()
if event.key() == QtCore.Qt.Key_Up:
self.runner.player_up()
self.update()
if event.key() == QtCore.Qt.Key_Down:
self.runner.player_down()
self.update()
def showEvent(self, event):
r = QRect(self.width() / 2, 0, self.width() / 2, self.height() / 2)
self.runner_painter.rect = r
self.tick_timer.start()
def closeEvent(self, event):
self.tick_timer.stop()
def paintEvent(self, event):
painter = QtGui.QPainter(self)
painter.setRenderHint(QtGui.QPainter.Antialiasing, True)
painter.drawText(100, 100,
"Fitness: {}".format(self.runner.total_ticks_alive))
self.runner_painter.paint(painter)
self.network_painter.paint(painter)
def tick(self):
self.runner_ai.tick()
self.runner_trainer.tick()
self.update()
self.genetic_algorithm.tick()
def sizeHint(self):
return QtCore.QSize(300, 300)
class NeuralNetworkDemoWidget(QtWidgets.QWidget):
"""
NeuralNetwork
"""
def __init__(self):
super(NeuralNetworkDemoWidget, self).__init__()
self.setWindowTitle("NeuralNetwork")
self.tick_timer = QtCore.QTimer()
self.tick_timer.setInterval(100)
self.tick_timer.timeout.connect(self.tick)
self.network = Network(5, [4, 2, 5], 4)
self.network.setup()
self.network_painter = NetworkPainter(self.network)
self.network_painter.rect = self.rect()
self.exported_weights = []
self.setCursor(QtCore.Qt.BlankCursor)
w = self.network.export_weights()
self.network.import_weights(w)
assert w == self.network.export_weights()
def keyPressEvent(self, event):
if event.key() == QtCore.Qt.Key_S:
self.exported_weights = self.network.export_weights()
res = QtWidgets.QFileDialog.getSaveFileName(self, "Save")
print(res)
if res[0]:
n = self.network.json()
with open(res[0], 'w') as fp:
json.dump(n, fp)
if event.key() == QtCore.Qt.Key_H:
self.network_painter.draw_output_value = not self.network_painter.draw_output_value
if event.key() == QtCore.Qt.Key_L:
# self.network.import_weights(self.exported_weights)
res = QFileDialog.getOpenFileName(self, "Load")
if res[0]:
with open(res[0], 'r') as fp:
data = json.load(fp)
self.set_network(Network.from_json(data))
if event.key() == QtCore.Qt.Key_Space:
self.give_network_random_input()
self.update()
def set_network(self, network):
self.network = network
self.network_painter.network = network
self.update()
def mousePressEvent(self, event):
pass
def mouseMoveEvent(self, event):
pass
def give_network_random_input(self):
data = []
for i in range(len(self.network.input_layer)):
v = -1 + random.random() * 2
data.append(v)
self.network.respond(data)
def showEvent(self, event):
self.tick_timer.start()
self.network_painter.rect = self.rect()
self.give_network_random_input()
def closeEvent(self, event):
self.tick_timer.stop()
def resizeEvent(self, event):
self.network_painter.rect = self.rect()
def paintEvent(self, event):
painter = QtGui.QPainter(self)
painter.setRenderHint(QtGui.QPainter.Antialiasing, True)
self.network_painter.paint(painter)
def tick(self):
self.update()
def sizeHint(self):
return QtCore.QSize(300, 300)