code: def sde(self):
          
          variance = float(self.variance.values)
          lengthscale = float(self.lengthscale.values)
          foo  = np.sqrt(3.)/lengthscale
          F    = np.array([[0, 1], [-foo**2, -2*foo]])
          L    = np.array([[0], [1]])
          Qc   = np.array([[12.*np.sqrt(3) / lengthscale**3 * variance]])
          H    = np.array([[1, 0]])
          Pinf = np.array([[variance, 0],
          [0,              3.*variance/(lengthscale**2)]])
          # Allocate space for the derivatives
          dF    = np.empty([F.shape[0],F.shape[1],2])
          dQc   = np.empty([Qc.shape[0],Qc.shape[1],2])
          dPinf = np.empty([Pinf.shape[0],Pinf.shape[1],2])
          # The partial derivatives
          dFvariance       = np.zeros([2,2])
          dFlengthscale    = np.array([[0,0],
          [6./lengthscale**3,2*np.sqrt(3)/lengthscale**2]])
          dQcvariance      = np.array([12.*np.sqrt(3)/lengthscale**3])
          dQclengthscale   = np.array([-3*12*np.sqrt(3)/lengthscale**4*variance])
          dPinfvariance    = np.array([[1,0],[0,3./lengthscale**2]])
          dPinflengthscale = np.array([[0,0],
          [0,-6*variance/lengthscale**3]])
          # Combine the derivatives
          dF[:,:,0]    = dFvariance
          dF[:,:,1]    = dFlengthscale
          dQc[:,:,0]   = dQcvariance
          dQc[:,:,1]   = dQclengthscale
          dPinf[:,:,0] = dPinfvariance
          dPinf[:,:,1] = dPinflengthscale
  
          return (F, L, Qc, H, Pinf, dF, dQc, dPinf)
docs: Return the state space representation of the covariance.