def step()

in gym_hil/envs/panda_arrange_boxes_gym_env.py [0:0]

• 13 lines of code
• 6 McCabe index (conditional complexity)

    def step(self, action: np.ndarray) -> Tuple[Dict[str, np.ndarray], float, bool, bool, Dict[str, Any]]:
        """Take a step in the environment."""
        # Apply the action to the robot
        self.apply_action(action)

        # Compute observation, reward and termination
        obs = self._compute_observation()
        rew = self._compute_reward()
        success = self._is_success()

        if self.reward_type == "sparse":
            success = rew == 1.0

        # Check if block is outside bounds
        block_pos = self._data.sensor("block1_pos").data
        exceeded_bounds = np.any(block_pos[:2] < (_SAMPLING_BOUNDS[0] - self.block_range - 0.05)) or np.any(
            block_pos[:2] > (_SAMPLING_BOUNDS[1] + self.block_range + 0.05)
        )

        terminated = bool(success or exceeded_bounds)

        return obs, rew, terminated, False, {"succeed": success}