Return the state space representation of the covariance.

def sde(self):
        """
        Return the state space representation of the covariance.
        """
        variance = float(self.variance.values)
        lengthscale = float(self.lengthscale)

        F  = np.array(((-1.0/lengthscale,),))
        L  = np.array(((1.0,),))
        Qc = np.array( ((2.0*variance/lengthscale,),) )
        H = np.array(((1.0,),))
        Pinf = np.array(((variance,),))
        P0 = Pinf.copy()

        dF = np.zeros((1,1,2));
        dQc = np.zeros((1,1,2));
        dPinf = np.zeros((1,1,2));

        dF[:,:,0] = 0.0
        dF[:,:,1] = 1.0/lengthscale**2

        dQc[:,:,0] = 2.0/lengthscale
        dQc[:,:,1] = -2.0*variance/lengthscale**2

        dPinf[:,:,0] = 1.0
        dPinf[:,:,1] = 0.0

        dP0 = dPinf.copy()

        return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0)