.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/hybrid_choice/config.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_hybrid_choice_config.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_hybrid_choice_config.py:


Configuration
=============

Central configuration for running estimation scripts.

This module defines the :class:`Config` dataclass, which gathers all high-level
options controlling the behavior of the estimation pipeline. A single instance
of :class:`Config` is typically created in a small configuration file (e.g.
`conf_01.py`, `conf_02.py`) and passed to the main execution routine.

The goal of this module is to provide a clear, typed, and immutable container
for experimental settings, so that the same codebase can be reused across
multiple configurations without duplication.

Michel Bierlaire
Thu Dec 25 2025, 08:08:37

.. GENERATED FROM PYTHON SOURCE LINES 20-55

.. code-block:: Python


    from dataclasses import dataclass
    from typing import Literal


    @dataclass(frozen=True)
    class Config:
        """Configuration of a single estimation run.

        Each field controls a specific modeling or estimation choice:

        - ``name``: Human-readable identifier for the configuration (used for logging
          and output naming).
        - ``latent_variables``: Specifies whether latent variables are included in the
          model (``"zero"``) or whether the full hybrid choice model with two latent
          variables is used (``"two"``).
        - ``choice_model``: Indicates whether a discrete choice model is included
          alongside the latent-variable measurement model (``"yes"`` or ``"no"``).
        - ``estimation``: Estimation paradigm, either Bayesian (``"bayes"``) or
          maximum likelihood (``"ml"``).
        - ``number_of_bayesian_draws_per_chain``: Number of posterior draws per MCMC
          chain when Bayesian estimation is used.
        - ``number_of_monte_carlo_draws``: Number of Monte Carlo draws used for
          numerical integration in maximum likelihood estimation.

        The dataclass is frozen to guarantee immutability during execution and
        improve reproducibility.
        """

        name: str
        latent_variables: Literal["zero", "two"]
        choice_model: Literal["yes", "no"]
        estimation: Literal["bayes", "ml"]
        number_of_bayesian_draws_per_chain: int
        number_of_monte_carlo_draws: int


.. _sphx_glr_download_auto_examples_hybrid_choice_config.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: config.ipynb <config.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: config.py <config.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: config.zip <config.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_