entries_model#

t3toolbox.fitting.entries_model(geometry, x, index, residual, regularizer=None)#
def entries_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
        residual:   NDArray,                 # r = entries(x) − y, shape W+C
        regularizer: typ.Any = None,         # optional regularizer, e.g. optimizers.IdentityRegularizer(λ)
) -> typ.Union[GaussNewtonModel, UniformGaussNewtonModel]:

The Gauss-Newton model of an all-modes entries least-squares objective at x, on geometry.

Identical to apply_model() but the measurements are tensor entries at integer grid points index (shape (d,)+W) rather than applies against probe vectors.

Parameters:
Return type:

t3toolbox.backend.common.typ.Union[GaussNewtonModel, UniformGaussNewtonModel]