ut3variations_to_t3variations
=============================

.. py:function:: t3toolbox.backend.ufv_conversions.ut3variations_to_t3variations(x)

   .. code-block:: python

      def ut3variations_to_t3variations(
              x: typ.Tuple[
                  NDArray,                          # tucker_variations,  (d,)+C+(nD, N)
                  NDArray,                          # tt_variations,      (d,)+C+(rL, nU, rR)
                  typ.Tuple[int, ...],              # shape
                  typ.Tuple[                        # (variations up, down, left, right) masks
                      NDArray, NDArray, NDArray, NDArray,
                  ],
              ],
      ) -> typ.Union[
          typ.Tuple[typ.Tuple[NDArray, ...], typ.Tuple[NDArray, ...]],  # (tucker_variations, tt_variations), if unstacked
          typ.Tuple,                                                    # else a nested tree (shape stack_shape) of those
      ]:


   Convert uniform ``UT3Variations`` ``.data`` to ragged ``T3Variations`` core-tuples (or a tree, if stacked).

   Variations twin of :py:func:`ut3frame_to_t3frame`. The physical mode dim is a prefix (slices ``[:Ni]``
   from ``shape``); the rank masks scatter, so they extract with ``np.argwhere`` (HOST numpy). The
   variation tt-core ``H_i`` has shape ``(rLi, nUi, rR(i+1))`` -- left/up/right masks index its three axes.