UT3Frame.random_orthogonal
==========================

.. py:method:: t3toolbox.uniform_frame_variations_format.UT3Frame.random_orthogonal(shape, tucker_ranks, tt_ranks, stack_shape = (), use_jax = False)
   :staticmethod:


   .. code-block:: python

      def random_orthogonal(
              shape:        typ.Sequence[int],   # (N0,...,N(d-1))
              tucker_ranks,                       # int | len-d seq | (d,)+stack array (the variety)
              tt_ranks,                           # int | len-(d+1) seq | (d+1,)+stack array
              stack_shape:  typ.Tuple[int, ...] = (),
              use_jax:      bool = False,
      ) -> 'UT3Frame':


   Orthogonal representation of a *random* uniform T3 -- a genuine random base point (orthogonal,
   consistent), not iid-random supercores. Equals ``from_ut3(UniformTuckerTensorTrain.randn(...))``.