def __init__()

in gym_hil/wrappers/hil_wrappers.py [0:0]

• 25 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self, env, ee_action_step_size, use_gripper=False):
        super().__init__(env)
        self.ee_action_step_size = ee_action_step_size
        self.use_gripper = use_gripper

        self._ee_step_size = np.array(
            [
                ee_action_step_size["x"],
                ee_action_step_size["y"],
                ee_action_step_size["z"],
            ]
        )
        num_actions = 3

        # Initialize action space bounds for the non-gripper case
        action_space_bounds_min = -np.ones(num_actions)
        action_space_bounds_max = np.ones(num_actions)

        if self.use_gripper:
            action_space_bounds_min = np.concatenate([action_space_bounds_min, [0.0]])
            action_space_bounds_max = np.concatenate([action_space_bounds_max, [2.0]])
            num_actions += 1

        ee_action_space = gym.spaces.Box(
            low=action_space_bounds_min,
            high=action_space_bounds_max,
            shape=(num_actions,),
            dtype=np.float32,
        )
        self.action_space = ee_action_space