Method step

humanoidverse/utils/noise_tool.py:67–69

(self)

        self.x[mask] = self.randn(torch.sum(mask)) * self.sigma / np.sqrt(2 * self.theta) + self.mu

    def step(self):
        self.x = self.x + self.theta * (self.mu - self.x) * self.dt + self.sigma * self.randn(*self.shape) * np.sqrt(self.dt)
        return self.x

class WhiteNoise(NoiseProcess):
    def __init__(self, shape: Tuple[int, ...], mu: float = 0, sigma: float = 1, **kwargs):