def create(self, env_id, seed=None):
try:
if (env_id == 'osim'):
from osim.env import RunEnv
env = RunEnv(visualize=True)
else:
env = gym.make(env_id)
print('making environment')
if seed:
env.seed(seed)
except gym.error.Error:
raise InvalidUsage(
"Attempted to look up malformed environment ID '{}'".format(
env_id))
instance_id = str(uuid.uuid4().hex)[:self.id_len]
self.envs[instance_id] = env
self.envs_id[instance_id] = env_id
return instance_id
class WrapperEnv():
def __init__(self,
game='l2r',
visualize=False,
max_obstacles=10,
skip_count=1):
self.env = RunEnv(visualize=visualize, max_obstacles=max_obstacles)
self.step_count = 0
self.old_observation = None
self.skip_count = 1 # skip_count # 4
self.last_x = 0
self.current_x = 0
self.observation_space_shape = (76, )
self.action_space = self.env.action_space
self.difficulty = 2
def obg(self, plain_obs):
# observation generator
# derivatives of observations extracted here.
processed_observation, self.old_observation = go(plain_obs,
self.old_observation,
step=self.step_count)
return np.array(processed_observation)
def process_action(self, action):
processed_action = [(v + 1.0) / 2 for v in action]
return processed_action
def step(self, action):
action = [float(action[i]) for i in range(len(action))]
action = self.process_action(action)
import math
for num in action:
if math.isnan(num):
print('NaN met', action)
raise RuntimeError('this is bullshit')
sr = 0
sp = 0
o, oo = [], []
d, i = 0, 0
self.last_x = self.current_x
for j in range(self.skip_count):
self.step_count += 1
oo, r, d, i = self.env.step(action)
self.current_x = oo[1]
headx = oo[22]
px = oo[1]
py = oo[2]
kneer = oo[7]
kneel = oo[10]
lean = min(0.3, max(0, px - headx - 0.15)) * 0.05
joint = sum([max(0, k - 0.1)
for k in [kneer, kneel]]) * 0.03 # * 0.03
penalty = lean + joint
o = self.obg(oo)
sr += r
sp += penalty
if d is True:
break
res = [o, sr, d, sp]
# res = [o, sr, d, i]
return res
def reset(self, difficulty=2):
self.difficulty = difficulty
self.step_count = 0
self.old_observation = None
oo = self.env.reset(difficulty=difficulty)
self.last_x = oo[1]
self.current_x = oo[1]
o = self.obg(oo)
return o
def seed(self, s):
self.env.seed(s)
