code: def step(self, a):
      self.do_simulation(a, self.frame_skip)
      pos_after = self.sim.data.qpos[2]
      data = self.sim.data
      uph_cost = (pos_after - 0) / self.model.opt.timestep
  
      quad_ctrl_cost = 0.1 * np.square(data.ctrl).sum()
      quad_impact_cost = 0.5e-6 * np.square(data.cfrc_ext).sum()
      quad_impact_cost = min(quad_impact_cost, 10)
      reward = uph_cost - quad_ctrl_cost - quad_impact_cost + 1
  
      if self.render_mode == "human":
          self.render()
      return (
          self._get_obs(),
          reward,
          False,
          False,
          dict(
              reward_linup=uph_cost,
              reward_quadctrl=-quad_ctrl_cost,
              reward_impact=-quad_impact_cost,
          ),
      )
  
file_path: gym/gym/envs/mujoco/humanoidstandup.py
imports: import numpy
  from gym import utils
  from gym.envs.mujoco import MuJocoPyEnv
  from gym.spaces import Box
label_desc: Use image node_id 3 for calling the HumanoidStandupEnv obj's underlying member method code with example usage: obj.step(a) and returns: self,  reward,  False,  False,  dict