def __init__(self, config, road, simulation, representation):
self.config = config
self.road = road
self.simulation = simulation
self.representation = representation
self.updateFrame = simulation.updateFrame
self.acc = 0
self.collect = Collect(config, road, simulation, representation)
class DataScience():
def __init__(self, config, road, simulation, representation):
self.config = config
self.road = road
self.simulation = simulation
self.representation = representation
self.updateFrame = simulation.updateFrame
self.acc = 0
self.collect = Collect(config, road, simulation, representation)
#self.ml = MachineLearning(collect)
#self.analize = Analize(collect)
def writeInput(self):
""" Guardar los parametros de entrada"""
self.collect.writeInput()
def writeOutput(self):
""" Guardar los parametros de salida"""
self.collect.writeOutput()
def update(self, dt):
""" Actualizar los valores de los parametros de salida"""
self.collecting(dt)
def collecting(self, dt):
""" Recaudar los parametros de salida"""
self.acc += dt
if self.acc >= self.updateFrame:
self.collect.showRoad()
self.collect.writeOutput()
#self.collect.showSpeedLimits()
self.acc = self.acc % (self.updateFrame + 0)