simopt.model
============

.. py:module:: simopt.model

.. autoapi-nested-parse::

   Base class for simulation models used in simulation optimization problems.





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

.. py:class:: Model(fixed_factors: dict | None = None)

   Bases: :py:obj:`abc.ABC`


   Base class for simulation models used in simulation-optimization problems.

   Each model defines the simulation logic behind a given problem instance.

   Initialize a model object.

   :param fixed_factors: Dictionary of user-specified model
                         factors.
   :type fixed_factors: dict | None, optional


   .. py:attribute:: class_name_abbr
      :type:  ClassVar[str]

      Short name of the model class.


   .. py:attribute:: class_name
      :type:  ClassVar[str]

      Long name of the model class.


   .. py:attribute:: config_class
      :type:  ClassVar[type[pydantic.BaseModel]]

      Configuration class for the model.


   .. py:attribute:: n_rngs
      :type:  ClassVar[int]

      Number of RNGs used to run a simulation replication.


   .. py:attribute:: n_responses
      :type:  ClassVar[int]

      Number of responses (performance measures).


   .. py:attribute:: config


   .. py:method:: name() -> str

      Name of model.



   .. py:method:: specifications() -> dict[str, dict]

      Details of each factor (for GUI, data validation, and defaults).



   .. py:property:: factors
      :type: dict


      Changeable factors of the simulation model.


   .. py:method:: model_created() -> None

      Hook called after the model is constructed.

      Subclasses can override this to use custom input models.



   .. py:method:: before_replicate(rng_list: list[mrg32k3a.mrg32k3a.MRG32k3a]) -> None
      :abstractmethod:


      Prepare the model just before generating a replication.

      :param rng_list: RNGs used to drive the simulation.
      :type rng_list: list[MRG32k3a]

      :raises NotImplementedError: If the subclass does not implement this hook.



   .. py:method:: replicate() -> tuple[dict, dict]
      :abstractmethod:


      Simulate a single replication for the current model factors.

      :param rng_list: List of random-number
                       generators used to generate a random replication.
      :type rng_list: list[``mrg32k3a.mrg32k3a.MRG32k3a``]

      :returns:     - dict: Performance measures of interest.
                    - dict: Gradient estimates for each response.
      :rtype: tuple