clophfit.testing.fitter_test_utils
==================================

.. py:module:: clophfit.testing.fitter_test_utils

.. autoapi-nested-parse::

   Shared utilities for fitter comparison tests and benchmarks.



Classes
-------

.. autoapisummary::

   clophfit.testing.fitter_test_utils.TecanFitCombination


Functions
---------

.. autoapisummary::

   clophfit.testing.fitter_test_utils.build_factorized_tecan_fit_combinations
   clophfit.testing.fitter_test_utils.build_tecan_fit_combinations
   clophfit.testing.fitter_test_utils.apply_tecan_combination
   clophfit.testing.fitter_test_utils.k_from_result
   clophfit.testing.fitter_test_utils.s_from_result
   clophfit.testing.fitter_test_utils.build_fitters


Module Contents
---------------

.. py:class:: TecanFitCombination

   Declarative description of one Tecan fitting workflow.


.. py:function:: build_factorized_tecan_fit_combinations(*, channels = (('1', ), ('2', ), ('1', '2')), prefits = ('huber', ), final_stages = ('huber', 'odr'), weightings = ('auto', ), outlier_handlings = (None, ))

   Build a systematic registry across explicit Tecan benchmark factors.


.. py:function:: build_tecan_fit_combinations(*, base_method = 'huber', include_odr = True, include_mcmc = False, mcmc_modes = ('single', ))

   Build named Tecan fit combinations for paired benchmark comparisons.


.. py:function:: apply_tecan_combination(ds, combination)

   Execute one Tecan fit combination on a fresh dataset copy.


.. py:function:: k_from_result(fr)

   Extract K value and stderr from fit result.


.. py:function:: s_from_result(fr, which)

   Extract S0 or S1 values per label if present in params.


.. py:function:: build_fitters(*, include_odr = True)

   Build dictionary of fitting methods for benchmarking.

   Returns a registry of named fitters using the unified ``fit_binding_glob``
   API with different method/reweight/remove_outliers combinations.

   :param include_odr: Whether to include ODR-based fitters (requires odrpack).
   :type include_odr: bool

   :returns: Named fitters mapping.
   :rtype: dict[str, Callable[[Dataset], FitResult[MiniT]]]