44 lines
1.3 KiB
Python
44 lines
1.3 KiB
Python
from typing import Tuple, Union
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import numpy as np
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from mp_env_api import MPEnvWrapper
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class MPWrapper(MPEnvWrapper):
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@property
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def active_obs(self):
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return np.hstack([
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[self.env.random_start] * self.env.n_links, # cos
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[self.env.random_start] * self.env.n_links, # sin
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[self.env.random_start] * self.env.n_links, # velocity
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[self.env.initial_width is None], # hole width
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# [self.env.hole_depth is None], # hole depth
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[True] * 2, # x-y coordinates of target distance
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[False] # env steps
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])
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# @property
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# def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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# return self._joint_angles.copy()
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#
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# @property
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# def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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# return self._angle_velocity.copy()
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@property
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def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.current_pos
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@property
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.current_vel
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@property
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def goal_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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raise ValueError("Goal position is not available and has to be learnt based on the environment.")
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@property
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def dt(self) -> Union[float, int]:
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return self.env.dt
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