TuckerTensorTrain.stack
=======================

.. py:method:: t3toolbox.tucker_tensor_train.TuckerTensorTrain.stack(xx)
   :staticmethod:


   .. code-block:: python

      def stack(
              xx, # array-like structure of nested tuples containing TuckerTensorTrains
      ) -> 'TuckerTensorTrain':  # (stacked_tucker_cores, stacked_tt_cores)


   Stacks an array-like tree of TuckerTensorTrains into one stacked TuckerTensorTrain.

   :param xx: TuckerTensorTrains to be stacked. All TuckerTensorTrains must have the same shape and ranks.
   :type xx: Array-like tree of nested tuples with TuckerTensorTrain leafs

   :returns: Stacked TuckerTensorTrain.
   :rtype: TuckerTensorTrain

   .. seealso:: :py:meth:`.TuckerTensorTrain.unstack`, :py:attr:`.TuckerTensorTrain.stack_shape`

   .. rubric:: Examples

   >>> import numpy as np
   >>> import t3toolbox.tucker_tensor_train as t3
   >>> import t3toolbox.corewise as cw
   >>> x = t3.TuckerTensorTrain.randn((14,15,16), (4,6,2), (1,4,2,1), stack_shape=(3,5))
   >>> xx = x.unstack()
   >>> print(len(xx))
   3
   >>> print(len(xx[0]))
   5
   >>> x2 = t3.TuckerTensorTrain.stack(xx)
   >>> print(cw.corewise_norm(cw.corewise_sub(x.data, x2.data)))
   0.0