TuckerTensorTrain.squash_tails
==============================

.. py:method:: t3toolbox.tucker_tensor_train.TuckerTensorTrain.squash_tails()

   .. code-block:: python

      def squash_tails(
              self,
      ) -> 'TuckerTensorTrain':


   Make leading and trailing TT ranks equal to 1 (``r0=rd=1``), without changing represented dense tensor.

   :returns: * *TuckerTensorTrain* -- Tucker tensor train with ``tt_ranks=(1,r1,...,r(d-1),1)``.
             * *See Also*
             * *---------*
             * :py:attr:`.TuckerTensorTrain.tt_ranks`

   .. rubric:: Examples

   >>> import numpy as np
   >>> import t3toolbox.tucker_tensor_train as t3
   >>> np.random.seed(0)
   >>> randn = np.random.randn
   >>> tucker_cores = (randn(2,3, 4,10), randn(2,3, 5,11), randn(2,3, 6,12))
   >>> tt_cores = (randn(2,3, 2,4,3), randn(2,3, 3,5,2), randn(2,3, 2,6,5))
   >>> x = t3.TuckerTensorTrain(tucker_cores, tt_cores)
   >>> print(x.tt_ranks)
   (2, 3, 2, 5)
   >>> x2 = x.squash_tails()
   >>> print(x2.tt_ranks)                  # leading/trailing bonds forced to 1
   (1, 3, 2, 1)
   >>> print(np.allclose(x.to_dense(), x2.to_dense()))   # same dense tensor
   True