t3_from_canonical
=================

.. py:function:: t3toolbox.backend.t3_conversions.t3_from_canonical(factors)

   .. code-block:: python

      def t3_from_canonical(
              factors: typ.Sequence[NDArray],  # len=d, elm_shape=stack_shape+(canonical_rank,Ni)
      ) -> typ.Tuple[
          typ.Tuple[NDArray, ...],  # tucker_cores. len=d, elm_shape=stack_shape+(canonical_rank,Ni)
          typ.Tuple[NDArray, ...],  # tt_cores.     len=d, superdiagonal, elm_shape=stack_shape+(cr,cr,cr)
      ]:


   Constructs Tucker tensor train from Canonical decomposition.