def step()

in robogym/wrappers/randomizations.py [0:0]

• 26 lines of code
• 8 McCabe index (conditional complexity)

    def step(self, action):
        obs, rew, done, info = self.env.step(action)

        # Simulate flipping somehow
        if self._side > 0:
            if self.unwrapped._random_state.uniform() > self._p_flip_pos:
                self._side = -self._side
        else:
            if self.unwrapped._random_state.uniform() > self._p_flip_neg:
                self._side = -self._side

        if self._side > 0:
            noise = self.unwrapped._random_state.exponential(
                1.0 / self._positive_lambda
            )
        else:
            noise = self.unwrapped._random_state.exponential(
                1.0 / self._negative_lambda
            )

        noise *= self._variance_multiplier

        if self._side < 0:
            # Rescale
            fraction = noise / self._orig_value
            noise = self._orig_value * (fraction / (1 + fraction))

        if self._side < 0:
            # Clip the noise if it's negative so that the simulation is stable
            noise = np.clip(noise, 0.0, self._orig_value / 2)

        self.unwrapped.sim.model.opt.timestep = self._bias_multiplier * (
            self._orig_value + self._side * noise
        )

        return self.observation(obs), rew, done, info