code: def L(self):
          r
          from scipy.linalg import cho_factor
          from numpy_sugar.linalg import ddot, sum2diag
  
          if self._L_cache is not None:
              return self._L_cache
  
          Q = self._cov["QS"][0][0]
          S = self._cov["QS"][1]
          B = dot(Q.T, ddot(self._site.tau, Q, left=True))
          sum2diag(B, 1.0 / S, out=B)
          self._L_cache = cho_factor(B, lower=True)[0]
          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}