def weights(self):

        n = self.n
        lambda_ = self.alpha**2 * (n +self.kappa) - n

        c = .5 / (n + lambda_)
        Wc = np.full(2*n + 1, c)
        Wm = np.full(2*n + 1, c)
        Wc[0] = lambda_ / (n + lambda_) + (1 - self.alpha**2 + self.beta)
        Wm[0] = lambda_ / (n + lambda_)

        return Wm, Wc
Computes the weights for the scaled unscented Kalman filter.
dataset/ETHPy150Open rlabbe/filterpy/filterpy/kalman/sigma_points.py/MerweScaledSigmaPoints.weights