entries_derivatives_model
=========================

.. py:function:: t3toolbox.fitting.entries_derivatives_model(geometry, x, index, pp, order, residual, weight = None, regularizer = None)

   .. code-block:: python

      def entries_derivatives_model(
              geometry,                            # MANIFOLD / COREWISE (or the UNIFORM_* twin for a uniform x)
              x:          typ.Union[t3.TuckerTensorTrain, ut3.UniformTuckerTensorTrain],   # the current point
              index:      NDArray,                 # int, shape=(d,)+W -- the grid points
              pp:         typ.Sequence[NDArray],   # perturbation vectors P, len=d, elm_shape=W+(Ni,)
              order:      int,
              residual:   NDArray,                 # RAW r = entries_derivatives(x) − y, shape (order+1)+W+C
              weight:     typ.Optional[typ.Any] = None,  # ORDER-only residual weight ω, (order+1,); None = 1
              regularizer: typ.Any = None,         # optional regularizer, e.g. optimizers.IdentityRegularizer(λ)
      ) -> typ.Union[GaussNewtonModel, UniformGaussNewtonModel]:


   The ``entries``-derivatives Gauss-Newton model -- like :py:func:`apply_derivatives_model` at integer
   grid points ``index``. Order-only ``weight`` (no mode axis -- mode weighting is probe-only).