pydynamicestimator.tests.baselines.inverter_baseline
====================================================

.. py:module:: pydynamicestimator.tests.baselines.inverter_baseline

.. autoapi-nested-parse::

   Shared configuration + runner for the inverter byte-identical baselines.

   Single source of truth for the ``IEEE39_bus_inverter`` baseline runs, imported by
   both ``create_baseline_inverter.py`` (which pickles the references) and the
   ``test_recur_{sim,est}_inverter.py`` gates (which compare against them). Keeping
   the config here prevents drift between baseline-creation and the tests -- any
   drift would surface as a spurious byte-identity failure rather than a real
   regression.

   This is **Phase 0** of ``docs/inverter_modernization_design.md``: the byte-identical
   safety net the whole inverter refactor rests on. Three cases gate the surface the
   ``fgcall``/``finit`` refactor touches:

   - ``sim_ld``  -- SIM, ``line_dyn=True`` (ODE; cvodes): 2 GridForming + 3
     GridFollowing + 5 SGs through the t=4.0 bus fault. Run at the production output
     step ``ts=1e-4`` but stored **decimated** (every ``SIM_LD_STRIDE``-th sample) so
     the pickle stays ~1 MB -- a byte-identical refactor matches at every sample, so
     the decimated reference is just as catching.
   - ``sim_alg`` -- SIM, ``line_dyn=False`` (algebraic network / DAE; idas): the
     distinct code path the eventual ``LCL_static`` realization will exercise.
   - ``est``     -- estimation (iekf) over the IEEE39_bus_inverter est model, which
     carries **both** a GridForming and a GridFollowing (``GFLI7_est`` at bus 36) so
     the GFL/PLL estimation path (qcall, algebraic weights, finit) is gated too.

   Baselines store only the ``x_full`` numpy arrays, not the whole DaeSim/DaeEst
   objects: under pytest's ``pythonpath="pydynamicestimator"`` +
   ``--import-mode=importlib``, ``system.DaeSim`` is reachable under two module paths,
   so whole-object pickling raises "it's not the same object". The arrays are all the
   gates compare anyway.



Attributes
----------

.. autoapisummary::

   pydynamicestimator.tests.baselines.inverter_baseline.FIXTURE_ROOT
   pydynamicestimator.tests.baselines.inverter_baseline._BASE
   pydynamicestimator.tests.baselines.inverter_baseline.SIM_LD_STRIDE
   pydynamicestimator.tests.baselines.inverter_baseline.T_END
   pydynamicestimator.tests.baselines.inverter_baseline.BASELINES
   pydynamicestimator.tests.baselines.inverter_baseline._COMMON
   pydynamicestimator.tests.baselines.inverter_baseline._INT_OPTS


Functions
---------

.. autoapisummary::

   pydynamicestimator.tests.baselines.inverter_baseline.make_inverter_baseline_config
   pydynamicestimator.tests.baselines.inverter_baseline.run_inverter_case


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

.. py:data:: FIXTURE_ROOT

.. py:data:: _BASE

.. py:data:: SIM_LD_STRIDE
   :value: 50


.. py:data:: T_END
   :value: 5.0


.. py:data:: BASELINES

.. py:data:: _COMMON

.. py:data:: _INT_OPTS

.. py:function:: make_inverter_baseline_config(case: str)

   Return the config for one baseline ``case`` (``sim_ld`` / ``sim_alg`` / ``est``).


.. py:function:: run_inverter_case(case: str) -> numpy.ndarray

   Run one baseline ``case`` and return the array the gate compares (the
   estimated trajectory for ``est``, otherwise the simulated trajectory;
   decimated for ``sim_ld``).