tv_precompute_entries_frame_sweep_jets
======================================

.. py:function:: t3toolbox.backend.sampling_derivatives.tv_precompute_entries_frame_sweep_jets(frame, index, pp, order)

   .. code-block:: python

      def tv_precompute_entries_frame_sweep_jets(
              frame:   typ.Tuple[
                  typ.Sequence[NDArray], typ.Sequence[NDArray],
                  typ.Sequence[NDArray], typ.Sequence[NDArray],
              ],                                      # = T3Frame.data = (U, O, P, Q)
              index:  NDArray,                        # int, shape=(d,)+W -- the grid points
              pp:     typ.Sequence[NDArray],          # perturbation vectors P, len=d, elm_shape=W+(Ni,)
              order:  int,                            # highest derivative order
      ) -> typ.Tuple[
          typ.Sequence[NDArray],  # xi_jets. len=d, elm_shape=(2,)+W+C+(nUi,)
          typ.Sequence[NDArray],  # mu_jets. len=d, elm_shape=(order+1,)+W+C+(rLi,)
      ]:                                              # lean frame sweep -- (xi, mu) only


   The **entries**-derivative frame sweep (lean): like :py:func:`tv_precompute_apply_frame_sweep_jets`
   but the up-index jet is formed by fiber-slicing the Tucker cores at ``index`` (order 0) + contracting
   ``P`` (order 1), so the variation gradient scatters onto the indexed rows. Also ``(xi, mu)`` only.