def reset_model()

in gym/gym/envs/mujoco/ant_obstaclesgen.py [0:0]

• 23 lines of code
• 10 McCabe index (conditional complexity)

    def reset_model(self):
        qpos = self.init_qpos + self.np_random.uniform(size=self.model.nq, low=-.1, high=.1)
        qvel = self.init_qvel + self.np_random.randn(self.model.nv) * .1

        # self.realgoal = 4
        if self.realgoal == 0:
            qpos[-11:] = np.array([80,0,0,80,0,0,0,0,0, 8, 24])
        if self.realgoal == 1:
            qpos[-11:] = np.array([0,0,0,80,0,0,80,0,0, 8, -24])
        if self.realgoal == 2:
            qpos[-11:] = np.array([0,80,0,80,80,0,0,0,0, 24, 24])
        if self.realgoal == 3:
            qpos[-11:] = np.array([0,0,0,80,80,0,0,80,0, 24, -24])
        if self.realgoal == 4:
            qpos[-11:] = np.array([0,0,0,80,80,80,0,0,0, 48, 0])

        if self.realgoal == 5:
            qpos[-11:] = np.array([0,0,80,80,80,80,0,0,0, 40, 24])
        if self.realgoal == 6:
            qpos[-11:] = np.array([0,0,0,80,80,80,0,0,80, 40, -24])
        if self.realgoal == 7:
            qpos[-11:] = np.array([80,80,0,80,0,0,0,0,0, 32, 16])
        if self.realgoal == 8:
            qpos[-11:] = np.array([0,0,0,80,0,0,80,80,0, 32, -16])

        self.set_state(qpos, qvel)
        return self._get_obs()