code: def L(self):
          r
          from numpy_sugar.linalg import ddot, sum2diag
  
          if self._L_cache is not None:
              return self._L_cache
  
          s = self._cov["scale"]
          d = self._cov["delta"]
          Q = self._cov["QS"][0][0]
          S = self._cov["QS"][1]
  
          ddot(self.A * self._site.tau, Q, left=True, out=self._NxR)
          B = dot(Q.T, self._NxR, out=self._RxR)
          B *= 1 - d
          sum2diag(B, 1.0 / S / s, out=B)
          self._L_cache = _cho_factor(B)
          return self._L_cache
docs: r"""Cholesky decomposition of :math:`\mathrm B`.
  
          .. math::
  
              \mathrm B = \mathrm Q^{\intercal}\tilde{\mathrm{T}}\mathrm Q
                  + \mathrm{S}^{-1}