code: def get_prediction(self, u=0):
          
  
          x = dot(self.F, self.x) + dot(self.B, u)
          P = self._alpha_sq * dot(dot(self.F, self.P), self.F.T) + self.Q
          return (x, P)
docs: Predicts the next state of the filter and returns it without
          altering the state of the filter.
  
          Parameters
          ----------
  
          u : np.array
              optional control input
  
          Returns
          -------
  
          (x, P) : tuple
              State vector and covariance array of the prediction.