def get_s(name):
sight = fc.get_car_sight(name)
ti = fc.get_ti(name)
mid = ti['mid']
while len(mid) < 5:
mid.append(mid[len(mid) - 1])
mid = np.array([mid[i * (len(mid) - 1) // 5] for i in range(5)])
mid = mid - np.array([len(fc.get_car_sight(name)[0]) / 2, 0])
s = np.reshape(mid, 10)
# right = ti['right']
# left = ti['left']
# if len(left) == 0:
# left.append([0,0])
# if len(right) == 0:
# right.append([wight-1,hight-1])
# while len(right)<5:
# right.append(right[len(right)-1])
# while len(left)<5:
# left.append(left[len(left)-1])
# right = np.array([right[i*(len(right)-1)//5] for i in range(5)])
# left = np.array([left[i*(len(left)-1)//5] for i in range(5)])
# s = np.concatenate([np.reshape(right,10), np.reshape(left,10)], 0)
return s
def get_r(name):
r, ti = 0, fc.get_ti(name)
mid = ti['mid']
sight = fc.get_car_sight(name)
if sight[mid[0][1]][mid[0][0]] < 0.5:
r = -1000
else:
r = -np.square(mid[0][0] - len(fc.get_car_sight(name)[0]) / 2)
#r -= np.square((100-fc.get_velocity(name))/50)
return r
def get_r(name):
sight = fc.get_car_sight(name)
wight = len(sight[0])
hight = len(sight)
r, ti = 0, fc.get_ti(name)
mid = ti['mid']
if sight[mid[0][1]][mid[0][0]] < 0.5:
r = -35
else:
r = -np.abs(mid[0][0] - wight / 2)
return r
def get_s(name):
sight = fc.get_car_sight(name)
wight = len(sight[0])
hight = len(sight)
ti = fc.get_ti(name)
mid = ti['mid']
while len(mid) < 5:
mid.append(mid[len(mid) - 1])
mid = np.array([mid[i * (len(mid) - 1) // 6] for i in range(5)])
mid = mid - np.array([wight / 2, 0])
mid = np.array([0, hight]) - mid
s = np.reshape(mid, 10)
s = np.concatenate([s, np.array([fc.get_velocity(name)])], 0)
return s
# while fc.get_time()-train_time<20:
# model.fit({input_map:train_sight[:len(train_y)-1],
# input_degree:train_degree[:len(train_y)-1],
# input_velocity:train_velocity[:len(train_y)-1]},
# {y:train_y[:len(train_y)-1]},
# n_epoch=1,batch_size=512,show_metric=True,shuffle=True)
# else:
# while fc.get_time()-train_time<20:
# fc.sleep(1)
train_time = fc.get_time()
while fc.get_time() - train_time < 20:
fc.sleep(1)
print(fc.get_time() - train_time)
mid = fc.get_ti("0")["mid"]
delta = 0
if len(mid) > 8:
delta = mid[0][0] - (wight - 1) / 2
else:
delta = (wight - 1) / 2
#r = np.exp(-np.power(delta,2)/36)/(1+np.exp(-(velocity-100)))
r = np.exp(-np.power(delta, 2) / 64) * np.exp(
-np.power(velocity - 100, 2) / 2000)
print(r)
r = r + 0.5 * out[0][2]
print(r)
if (fc.get_time() - reset_time > 50):
train_right = []
train_state = []
train_example_ctrl = []
train_y = []
degree = 0
velocity = 100
times = 0
fc.set_time_speed(1)
fc.start()
reset_time = fc.get_time()
while True:
ti = fc.get_ti("0")
right = ti['right']
left = ti['left']
if len(left) == 0:
left.append([0, 0])
if len(right) == 0:
right.append([wight - 1, hight - 1])
while len(right) < 5:
right.append(right[len(right) - 1])
while len(left) < 5:
left.append(left[len(left) - 1])
right = np.array([right[i * (len(right) - 1) // 5] for i in range(5)])
left = np.array([left[i * (len(left) - 1) // 5] for i in range(5)])