sumsq_over_samples
==================

.. py:function:: t3toolbox.backend.fitting.sumsq_over_samples(out, n_w)

   .. code-block:: python

      def sumsq_over_samples(
              out:    NDArray,    # scalar-output forward/residual, shape W+C (apply / entries)
              n_w:    int,        # number of leading sample-stack (W) axes
      ) -> NDArray:               # sum of squares over W, keeping the frame stack C


   The ``‖·‖²`` reduction for the scalar-output (apply / entries) kinds: sum ``out**2`` over the
   leading ``n_w`` sample axes, keeping the frame stack ``C``. Used for both the objective ``c = ½‖r‖²``
   and the model's quadratic term ``½‖𝒥 Π p‖²``.