compute_deta_jets_trs
=====================

.. py:function:: t3toolbox.backend.sampling_derivatives.compute_deta_jets_trs(var_tt_cores, left_tt_cores, right_tt_cores, mu_jets, nu_jets, sigma_jets, tau_jets, trs)

   .. code-block:: python

      def compute_deta_jets_trs(
              var_tt_cores:   typ.Sequence[NDArray],  # dG. len=d, elm_shape=K+C+(rLi,nUi,rR(i+1))
              left_tt_cores:  typ.Sequence[NDArray],  # P.  len=d, elm_shape=C+(rLi,nUi,rL(i+1))
              right_tt_cores: typ.Sequence[NDArray],  # Q.  len=d, elm_shape=C+(rRi,nUi,rR(i+1))
              mu_jets:        typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+C+(rLi,)
              nu_jets:        typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+C+(rR(i+1),)
              sigma_jets:     typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+K+C+(rR(i+1),)
              tau_jets:       typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+K+C+(rL(i+1),)
              trs:            NDArray,                # binomial tensor, shape=(order+1,order+1,order+1)
      ) -> typ.Tuple[NDArray, ...]:                   # deta_jets. len=d, elm_shape=(order+1,)+W+K+C+(nUi,)


   Variation-downward edge-variable jets deta (the jet-ified Algorithm-7 deta combine).

   ``deta_i = sigma_{i-1} Q_i nu_i + mu_{i-1} dG_i nu_i + mu_{i-1} P_i tau_i`` -- three combines
   (``'trs,rWCa,Caib,sWCb->tWCi'``), mode ``i`` free.