def predict(self, X, results_file):
ret = LinearModel.predict(self, X)
pred = self._sigmoid(ret)
fp = open(results_file, 'w')
for v in pred.flat:
print >> fp, v
fp.close()
def main():
print("main started")
samples, labels = load_trainingset()
# Build a model using a class, and after the compilation we'll start the training
model = LinearModel("my_model")
model.compile_model()
model.training(samples, labels)
# Evaluate a sample using the model
print(model.predict([30.0]))
print("main finish")
class Driver(object):
'''
A driver object for the SCRC
'''
def __init__(self, args):
'''Constructor'''
self.parser = msgParser.MsgParser()
self.state = carState.CarState()
self.control = carControl.CarControl()
self.state_size = 20
self.action_size = 3
self.model = LinearModel(args.replay_size, self.state_size, self.action_size)
self.enable_training = args.enable_training
self.enable_exploration = args.enable_exploration
self.show_sensors = args.show_sensors
self.exploration_decay_steps = args.exploration_decay_steps
self.exploration_rate_start = args.exploration_rate_start
self.exploration_rate_end = args.exploration_rate_end
from wheel import Wheel
self.wheel = Wheel(args.joystick_nr, args.autocenter, args.gain, args.min_level, args.max_level, args.min_force)
self.steer_lock = 0.785398
self.max_speed = 100
#from plotlinear import PlotLinear
#self.plot = PlotLinear(self.model, ['Speed', 'Angle', 'TrackPos'], ['Steer', 'Accel', 'Brake'])
if self.show_sensors:
from sensorstats import Stats
self.stats = Stats(inevery=8)
self.reset()
def init(self):
'''Return init string with rangefinder angles'''
self.angles = [0 for x in range(19)]
for i in range(5):
self.angles[i] = -90 + i * 15
self.angles[18 - i] = 90 - i * 15
for i in range(5, 9):
self.angles[i] = -20 + (i-5) * 5
self.angles[18 - i] = 20 - (i-5) * 5
return self.parser.stringify({'init': self.angles})
def getState(self):
#state = np.array(self.state.getTrack())
state = np.array(self.state.getTrack() + [self.state.getSpeedX()])
assert state.shape == (self.state_size,)
return state
def getTerminal(self):
return np.all(np.array(self.state.getTrack()) == -1)
def getEpsilon(self):
# calculate decaying exploration rate
if self.total_train_steps < self.exploration_decay_steps:
return self.exploration_rate_start - self.total_train_steps * (self.exploration_rate_start - self.exploration_rate_end) / self.exploration_decay_steps
else:
return self.exploration_rate_end
def drive(self, msg):
# parse incoming message
self.state.setFromMsg(msg)
# by default predict all controls by model
state = self.getState()
steer, accel, brake = self.model.predict(state)
self.control.setSteer(max(-1, min(1, steer)))
self.control.setAccel(max(0, min(1, accel)))
#self.control.setBrake(max(0, min(1, brake)))
# if not out of track turn the wheel according to model
terminal = self.getTerminal()
events = self.wheel.getEvents()
for event in events:
if self.wheel.isButtonDown(event, 0) or self.wheel.isButtonDown(event, 8):
self.control.setGear(-1)
elif self.wheel.isButtonDown(event, 1) or self.wheel.isButtonDown(event, 9):
self.control.setGear(1)
if self.control.getGear() >= 0:
self.gear()
# replace random exploration with user assistance
epsilon = self.getEpsilon()
# show sensors
if self.show_sensors:
self.state.botcontrol = 1 - epsilon
self.state.mancontrol = (self.control.getGear() == -1)
self.stats.update(self.state)
print "epsilon: ", epsilon, "\treplay: ", self.model.count
if (self.enable_training and terminal) or self.control.getGear() == -1 or (self.enable_exploration and random.random() < epsilon):
if terminal or self.control.getGear() == -1:
self.wheel.resetForce()
self.control.setSteer(self.wheel.getWheel())
self.control.setAccel(self.wheel.getAccel())
self.control.setBrake(self.wheel.getBrake())
if self.enable_training and not terminal and self.control.getGear() != -1:
action = (self.control.getSteer(), self.control.getAccel(), self.control.getBrake())
self.model.add(state, action)
self.model.train()
#self.plot.update()
else:
if terminal:
self.steer()
self.speed()
else:
steer = self.control.getSteer()
assert -1 <= steer <= 1
wheel = self.wheel.getWheel()
#print "steer:", steer, "wheel:", wheel
self.wheel.generateForce(steer - wheel)
self.total_train_steps += 1
return self.control.toMsg()
def steer(self):
angle = self.state.angle
dist = self.state.trackPos
self.control.setSteer((angle - dist*0.5)/self.steer_lock)
def speed(self):
speed = self.state.getSpeedX()
accel = self.control.getAccel()
if speed < self.max_speed:
print "speed < max_speed", speed, self.max_speed
accel += 0.1
if accel > 1:
accel = 1.0
else:
print "speed >= max_speed", speed, self.max_speed
accel -= 0.1
if accel < 0:
accel = 0.0
self.control.setAccel(accel)
def gear(self):
'''
rpm = self.state.getRpm()
gear = self.state.getGear()
if rpm > 7000:
gear += 1
'''
speed = self.state.getSpeedX()
gear = self.state.getGear()
if speed < 25:
gear = 1
elif 30 < speed < 55:
gear = 2
elif 60 < speed < 85:
gear = 3
elif 90 < speed < 115:
gear = 4
elif 120 < speed < 145:
gear = 5
elif speed > 150:
gear = 6
self.control.setGear(gear)
def onShutDown(self):
pass
def onRestart(self):
self.episode += 1
print "Episode", self.episode
def reset(self):
self.wheel.resetForce()
self.enable_training = True
self.total_train_steps = 0
self.model.reset()
self.episode = 0
self.onRestart()
def test_mode(self):
self.total_train_steps = self.exploration_decay_steps
self.enable_training = False
def predict(self, X):
ret = LinearModel.predict(self, X)
return self._sigmoid(ret)
def predict(self, X, results_file):
pred = LinearModel.predict(self, X)
fp = open(results_file, 'w')
for v in pred.flat:
print >> fp, v
fp.close()
from model_evaluation import r_squared
data = pd.read_csv("boston_house_price.txt", sep='|')
data = data[["LSTAT", "RM", "PTRATIO", "INDUS", "MEDV"]].values
data = (data - np.min(data)) / (np.max(data) - np.min(data))
N = data.shape[0]
RSQ = []
for step in range(1):
np.random.shuffle(data)
train = data[:int(N * 0.7), :]
test = data[int(N * 0.7):, :]
X_train = train[:, :-1]
Y_train = train[:, [-1]]
X_test = test[:, :-1]
Y_test = test[:, [-1]]
n_feat = X_train.shape[1]
model = LinearModel(n_feat)
model.training(X_train, Y_train, alpha=1.0, eps=0.001)
hatY_train = model.predict(X_train)
hatY_test = model.predict(X_test)
r1 = r_squared(Y_train, hatY_train)
r2 = r_squared(Y_test, hatY_test)
print(r1, r2)
sys.stdout.flush()
class Driver(object):
'''
A driver object for the SCRC
'''
def __init__(self, args):
'''Constructor'''
self.parser = msgParser.MsgParser()
self.state = carState.CarState()
self.control = carControl.CarControl()
self.state_size = 20
self.action_size = 3
self.model = LinearModel(args.replay_size, self.state_size,
self.action_size)
self.enable_training = args.enable_training
self.enable_exploration = args.enable_exploration
self.show_sensors = args.show_sensors
self.exploration_decay_steps = args.exploration_decay_steps
self.exploration_rate_start = args.exploration_rate_start
self.exploration_rate_end = args.exploration_rate_end
from wheel import Wheel
self.wheel = Wheel(args.joystick_nr, args.autocenter, args.gain,
args.min_level, args.max_level, args.min_force)
self.steer_lock = 0.785398
self.max_speed = 100
#from plotlinear import PlotLinear
#self.plot = PlotLinear(self.model, ['Speed', 'Angle', 'TrackPos'], ['Steer', 'Accel', 'Brake'])
if self.show_sensors:
from sensorstats import Stats
self.stats = Stats(inevery=8)
self.reset()
def init(self):
'''Return init string with rangefinder angles'''
self.angles = [0 for x in range(19)]
for i in range(5):
self.angles[i] = -90 + i * 15
self.angles[18 - i] = 90 - i * 15
for i in range(5, 9):
self.angles[i] = -20 + (i - 5) * 5
self.angles[18 - i] = 20 - (i - 5) * 5
return self.parser.stringify({'init': self.angles})
def getState(self):
#state = np.array(self.state.getTrack())
state = np.array(self.state.getTrack() + [self.state.getSpeedX()])
assert state.shape == (self.state_size, )
return state
def getTerminal(self):
return np.all(np.array(self.state.getTrack()) == -1)
def getEpsilon(self):
# calculate decaying exploration rate
if self.total_train_steps < self.exploration_decay_steps:
return self.exploration_rate_start - self.total_train_steps * (
self.exploration_rate_start -
self.exploration_rate_end) / self.exploration_decay_steps
else:
return self.exploration_rate_end
def drive(self, msg):
# parse incoming message
self.state.setFromMsg(msg)
# by default predict all controls by model
state = self.getState()
steer, accel, brake = self.model.predict(state)
self.control.setSteer(max(-1, min(1, steer)))
self.control.setAccel(max(0, min(1, accel)))
#self.control.setBrake(max(0, min(1, brake)))
# if not out of track turn the wheel according to model
terminal = self.getTerminal()
events = self.wheel.getEvents()
for event in events:
if self.wheel.isButtonDown(event, 0) or self.wheel.isButtonDown(
event, 8):
self.control.setGear(-1)
elif self.wheel.isButtonDown(event, 1) or self.wheel.isButtonDown(
event, 9):
self.control.setGear(1)
if self.control.getGear() >= 0:
self.gear()
# replace random exploration with user assistance
epsilon = self.getEpsilon()
# show sensors
if self.show_sensors:
self.state.botcontrol = 1 - epsilon
self.state.mancontrol = (self.control.getGear() == -1)
self.stats.update(self.state)
print "epsilon: ", epsilon, "\treplay: ", self.model.count
if (self.enable_training
and terminal) or self.control.getGear() == -1 or (
self.enable_exploration and random.random() < epsilon):
if terminal or self.control.getGear() == -1:
self.wheel.resetForce()
self.control.setSteer(self.wheel.getWheel())
self.control.setAccel(self.wheel.getAccel())
self.control.setBrake(self.wheel.getBrake())
if self.enable_training and not terminal and self.control.getGear(
) != -1:
action = (self.control.getSteer(), self.control.getAccel(),
self.control.getBrake())
self.model.add(state, action)
self.model.train()
#self.plot.update()
else:
if terminal:
self.steer()
self.speed()
else:
steer = self.control.getSteer()
assert -1 <= steer <= 1
wheel = self.wheel.getWheel()
#print "steer:", steer, "wheel:", wheel
self.wheel.generateForce(steer - wheel)
self.total_train_steps += 1
return self.control.toMsg()
def steer(self):
angle = self.state.angle
dist = self.state.trackPos
self.control.setSteer((angle - dist * 0.5) / self.steer_lock)
def speed(self):
speed = self.state.getSpeedX()
accel = self.control.getAccel()
if speed < self.max_speed:
print "speed < max_speed", speed, self.max_speed
accel += 0.1
if accel > 1:
accel = 1.0
else:
print "speed >= max_speed", speed, self.max_speed
accel -= 0.1
if accel < 0:
accel = 0.0
self.control.setAccel(accel)
def gear(self):
'''
rpm = self.state.getRpm()
gear = self.state.getGear()
if rpm > 7000:
gear += 1
'''
speed = self.state.getSpeedX()
gear = self.state.getGear()
if speed < 25:
gear = 1
elif 30 < speed < 55:
gear = 2
elif 60 < speed < 85:
gear = 3
elif 90 < speed < 115:
gear = 4
elif 120 < speed < 145:
gear = 5
elif speed > 150:
gear = 6
self.control.setGear(gear)
def onShutDown(self):
pass
def onRestart(self):
self.episode += 1
print "Episode", self.episode
def reset(self):
self.wheel.resetForce()
self.enable_training = True
self.total_train_steps = 0
self.model.reset()
self.episode = 0
self.onRestart()
def test_mode(self):
self.total_train_steps = self.exploration_decay_steps
self.enable_training = False
class Driver(object):
'''
A driver object for the SCRC
'''
def __init__(self, args):
'''Constructor'''
self.WARM_UP = 0
self.QUALIFYING = 1
self.RACE = 2
self.UNKNOWN = 3
self.stage = args.stage
self.parser = msgParser.MsgParser()
self.state = carState.CarState()
self.control = carControl.CarControl()
self.state_size = 3
self.action_size = 3
self.model = LinearModel(args.replay_size, self.state_size,
self.action_size)
self.steer_lock = 0.785398
self.max_speed = 100
self.enable_training = args.enable_training
self.enable_exploration = args.enable_exploration
self.show_sensors = args.show_sensors
self.total_train_steps = 0
self.exploration_decay_steps = args.exploration_decay_steps
self.exploration_rate_start = args.exploration_rate_start
self.exploration_rate_end = args.exploration_rate_end
self.episode = 0
self.onRestart()
#from plotlinear import PlotLinear
#self.plot = PlotLinear(self.model, ['Speed', 'Angle', 'TrackPos'], ['Steer', 'Accel', 'Brake'])
if self.show_sensors:
from sensorstats import Stats
self.stats = Stats(inevery=8)
def init(self):
'''Return init string with rangefinder angles'''
self.angles = [0 for x in range(19)]
for i in range(5):
self.angles[i] = -90 + i * 15
self.angles[18 - i] = 90 - i * 15
for i in range(5, 9):
self.angles[i] = -20 + (i - 5) * 5
self.angles[18 - i] = 20 - (i - 5) * 5
return self.parser.stringify({'init': self.angles})
def getState(self):
state = np.array([
self.state.getSpeedX(),
self.state.getAngle(),
self.state.getTrackPos()
])
assert state.shape == (self.state_size, )
return state
def getTerminal(self):
return np.all(np.array(self.state.getTrack()) == -1)
def getEpsilon(self):
# calculate decaying exploration rate
if self.total_train_steps < self.exploration_decay_steps:
return self.exploration_rate_start - self.total_train_steps * (
self.exploration_rate_start -
self.exploration_rate_end) / self.exploration_decay_steps
else:
return self.exploration_rate_end
def drive(self, msg):
# parse incoming message
self.state.setFromMsg(msg)
# show sensors
if self.show_sensors:
self.stats.update(self.state)
# during exploration use hard-coded algorithm
state = self.getState()
terminal = self.getTerminal()
epsilon = self.getEpsilon()
print "epsilon: ", epsilon, "\treplay: ", self.model.count
if terminal or (self.enable_exploration and random.random() < epsilon):
self.steer()
self.speed()
self.gear()
if self.enable_training:
action = (self.control.getSteer(), self.control.getAccel(),
self.control.getBrake())
self.model.add(state, action)
self.model.train()
#self.plot.update()
else:
steer, accel, brake = self.model.predict(state)
#print "steer:", steer, "accel:", accel, "brake:", brake
self.control.setSteer(steer)
self.control.setAccel(accel)
self.control.setBrake(brake)
self.gear()
self.total_train_steps += 1
return self.control.toMsg()
def steer(self):
angle = self.state.angle
dist = self.state.trackPos
self.control.setSteer((angle - dist * 0.5) / self.steer_lock)
def gear(self):
rpm = self.state.getRpm()
gear = self.state.getGear()
if self.prev_rpm == None:
up = True
else:
if (self.prev_rpm - rpm) < 0:
up = True
else:
up = False
if up and rpm > 7000:
gear += 1
if not up and rpm < 3000:
gear -= 1
'''
speed = self.state.getSpeedX()
if speed < 30:
gear = 1
elif speed < 60:
gear = 2
elif speed < 90:
gear = 3
elif speed < 120:
gear = 4
elif speed < 150:
gear = 5
else:
gear = 6
'''
self.control.setGear(gear)
def speed(self):
speed = self.state.getSpeedX()
accel = self.control.getAccel()
if speed < self.max_speed:
accel += 0.1
if accel > 1:
accel = 1.0
else:
accel -= 0.1
if accel < 0:
accel = 0.0
self.control.setAccel(accel)
def onShutDown(self):
pass
def onRestart(self):
self.prev_rpm = None
self.episode += 1
print "Episode", self.episode
class Driver(object):
'''
A driver object for the SCRC
'''
def __init__(self, args):
'''Constructor'''
self.parser = msgParser.MsgParser()
self.state = carState.CarState()
self.control = carControl.CarControl()
assert args.load_weights is not None, "Use --load_weights"
self.state_fields = args.state_fields
self.state_size = len(self.state_fields)
self.action_size = 3
self.model = LinearModel(args.replay_size, self.state_size, self.action_size)
self.model.load(args.load_weights)
self.episode = 0
self.onRestart()
self.show_sensors = args.show_sensors
if self.show_sensors:
from sensorstats import Stats
self.stats = Stats(inevery=8)
def init(self):
'''Return init string with rangefinder angles'''
self.angles = [0 for x in range(19)]
for i in range(5):
self.angles[i] = -90 + i * 15
self.angles[18 - i] = 90 - i * 15
for i in range(5, 9):
self.angles[i] = -20 + (i-5) * 5
self.angles[18 - i] = 20 - (i-5) * 5
return self.parser.stringify({'init': self.angles})
def drive(self, msg):
# parse incoming message
self.state.setFromMsg(msg)
# show sensors
if self.show_sensors:
self.stats.update(self.state)
state = np.array(sum(self.state.sensors.itervalues(), []), dtype=np.float)
state = state[self.state_fields]
#state = self.state.getTrack()
#state = [self.state.getAngle(), self.state.getSpeedX(), self.state.getTrackPos()]
steer, accel, brake = self.model.predict(state)
self.control.setSteer(steer)
self.control.setAccel(accel)
#self.control.setBrake(brake)
self.gear()
return self.control.toMsg()
def gear(self):
'''
rpm = self.state.getRpm()
gear = self.state.getGear()
if rpm > 7000:
gear += 1
'''
speed = self.state.getSpeedX()
gear = self.state.getGear()
if speed < 25:
gear = 1
elif 30 < speed < 55:
gear = 2
elif 60 < speed < 85:
gear = 3
elif 90 < speed < 115:
gear = 4
elif 120 < speed < 145:
gear = 5
elif speed > 150:
gear = 6
self.control.setGear(gear)
def onShutDown(self):
pass
def onRestart(self):
self.episode += 1
print "Episode", self.episode
class Driver(object):
'''
A driver object for the SCRC
'''
def __init__(self, args):
'''Constructor'''
self.WARM_UP = 0
self.QUALIFYING = 1
self.RACE = 2
self.UNKNOWN = 3
self.stage = args.stage
self.parser = msgParser.MsgParser()
self.state = carState.CarState()
self.control = carControl.CarControl()
self.state_size = 3
self.action_size = 3
self.model = LinearModel(args.replay_size, self.state_size, self.action_size)
self.steer_lock = 0.785398
self.max_speed = 100
self.enable_training = args.enable_training
self.enable_exploration = args.enable_exploration
self.show_sensors = args.show_sensors
self.total_train_steps = 0
self.exploration_decay_steps = args.exploration_decay_steps
self.exploration_rate_start = args.exploration_rate_start
self.exploration_rate_end = args.exploration_rate_end
self.episode = 0
self.onRestart()
#from plotlinear import PlotLinear
#self.plot = PlotLinear(self.model, ['Speed', 'Angle', 'TrackPos'], ['Steer', 'Accel', 'Brake'])
if self.show_sensors:
from sensorstats import Stats
self.stats = Stats(inevery=8)
def init(self):
'''Return init string with rangefinder angles'''
self.angles = [0 for x in range(19)]
for i in range(5):
self.angles[i] = -90 + i * 15
self.angles[18 - i] = 90 - i * 15
for i in range(5, 9):
self.angles[i] = -20 + (i-5) * 5
self.angles[18 - i] = 20 - (i-5) * 5
return self.parser.stringify({'init': self.angles})
def getState(self):
state = np.array([self.state.getSpeedX(), self.state.getAngle(), self.state.getTrackPos()])
assert state.shape == (self.state_size,)
return state
def getTerminal(self):
return np.all(np.array(self.state.getTrack()) == -1)
def getEpsilon(self):
# calculate decaying exploration rate
if self.total_train_steps < self.exploration_decay_steps:
return self.exploration_rate_start - self.total_train_steps * (self.exploration_rate_start - self.exploration_rate_end) / self.exploration_decay_steps
else:
return self.exploration_rate_end
def drive(self, msg):
# parse incoming message
self.state.setFromMsg(msg)
# show sensors
if self.show_sensors:
self.stats.update(self.state)
# during exploration use hard-coded algorithm
state = self.getState()
terminal = self.getTerminal()
epsilon = self.getEpsilon()
print "epsilon: ", epsilon, "\treplay: ", self.model.count
if terminal or (self.enable_exploration and random.random() < epsilon):
self.steer()
self.speed()
self.gear()
if self.enable_training:
action = (self.control.getSteer(), self.control.getAccel(), self.control.getBrake())
self.model.add(state, action)
self.model.train()
#self.plot.update()
else:
steer, accel, brake = self.model.predict(state)
#print "steer:", steer, "accel:", accel, "brake:", brake
self.control.setSteer(steer)
self.control.setAccel(accel)
self.control.setBrake(brake)
self.gear()
self.total_train_steps += 1
return self.control.toMsg()
def steer(self):
angle = self.state.angle
dist = self.state.trackPos
self.control.setSteer((angle - dist*0.5)/self.steer_lock)
def gear(self):
rpm = self.state.getRpm()
gear = self.state.getGear()
if self.prev_rpm == None:
up = True
else:
if (self.prev_rpm - rpm) < 0:
up = True
else:
up = False
if up and rpm > 7000:
gear += 1
if not up and rpm < 3000:
gear -= 1
'''
speed = self.state.getSpeedX()
if speed < 30:
gear = 1
elif speed < 60:
gear = 2
elif speed < 90:
gear = 3
elif speed < 120:
gear = 4
elif speed < 150:
gear = 5
else:
gear = 6
'''
self.control.setGear(gear)
def speed(self):
speed = self.state.getSpeedX()
accel = self.control.getAccel()
if speed < self.max_speed:
accel += 0.1
if accel > 1:
accel = 1.0
else:
accel -= 0.1
if accel < 0:
accel = 0.0
self.control.setAccel(accel)
def onShutDown(self):
pass
def onRestart(self):
self.prev_rpm = None
self.episode += 1
print "Episode", self.episode
