ut3frame_to_t3frame
===================

.. py:function:: t3toolbox.backend.ufv_conversions.ut3frame_to_t3frame(x)

   .. code-block:: python

      def ut3frame_to_t3frame(
              x: typ.Tuple[
                  NDArray,                          # up_tucker_supercore
                  NDArray,                          # down_tt_supercore
                  NDArray,                          # left_tt_supercore
                  NDArray,                          # right_tt_supercore
                  typ.Tuple[int, ...],              # shape
                  typ.Tuple[                        # (up_mask, down_mask, frame_left_mask, frame_right_mask)
                      NDArray, NDArray, NDArray, NDArray,
                  ],
              ],
      ) -> typ.Union[
          typ.Tuple[typ.Tuple[NDArray, ...], ...],  # (up_cores, down_cores, left_cores, right_cores), if unstacked
          typ.Tuple,                                # else a nested tree (shaped like stack_shape) of those
      ]:


   Convert a uniform UT3Frame ``.data`` to ragged ``T3Frame`` core-tuples (or a nested tree, if stacked).

   The physical mode dims are a contiguous prefix, so they slice ``[:Ni]`` (from the ``shape`` ints, no
   argwhere); only the *rank* masks scatter, so they are extracted with ``np.argwhere`` (HOST numpy --
   masks are host). The supercores may be jax; advanced-indexing them with the host int indices is fine.