def predict(self):
        """ Predict next position. """

        N = self.N
        for i, s in enumerate(self.sigmas):
           self.sigmas[i] = self.fx(s, self.dt)

        e = multivariate_normal(self.mean, self.Q, N)
        self.sigmas += e
        #self.x = np.mean(self.sigmas , axis=0)

        P = 0
        for s in self.sigmas:
            sx = self.x - s
            P += outer(sx, sx)

        self.P = P / (N-1)
dataset/ETHPy150Open rlabbe/filterpy/filterpy/kalman/ensemble_kalman_filter.py/EnsembleKalmanFilter.predict/swapped operands of `-`