.. _api_reference:

=============
API Reference
=============

This is the class and function reference of ddop.

.. _newsvendor_ref:

:mod:`ddop.newsvendor`: Newsvendor decision making
===================================================

The ``ddop.newsvendor`` module contains different newsvendor approaches for
decision making.

.. automodule:: ddop.newsvendor
    :no-members:
    :no-inherited-members:

.. currentmodule:: ddop.newsvendor

Sample Average Approximation (SAA)
-----------------------------------

.. autosummary::
    :toctree: modules/auto_generated/
    :template: class.rst

    SampleAverageApproximationNewsvendor


Weighted SAA (wSAA)
----------------------

.. autosummary::
    :toctree: modules/auto_generated/
    :template: class.rst

    DecisionTreeWeightedNewsvendor
    RandomForestWeightedNewsvendor
    KNeighborsWeightedNewsvendor
    GaussianWeightedNewsvendor


Empirical Risk Minimization (ERM)
---------------------------------

.. autosummary::
    :toctree: modules/auto_generated/
    :template: class.rst

    LinearRegressionNewsvendor
    DeepLearningNewsvendor


------------------------------------------------------------

.. _metrics_ref:

:mod:`ddop.metrics`: Evaluation metrics
========================================

The ``ddop.metrics`` module includes different performance metrics that can be used for model selection and
evaluation.

.. automodule:: ddop.metrics
    :no-members:
    :no-inherited-members:

.. currentmodule:: ddop.metrics

.. autosummary::
    :toctree: modules/auto_generated/

    total_costs
    average_costs
    prescriptiveness_score

All performance metrics can also be used with scikit-learn model selection tools. However, therefore
a proper scoring object has to be generated by using the make_scorer function.

.. autosummary::
    :toctree: modules/auto_generated/

    make_scorer

Moreover, the module contains a function to calculate the pairwise costs.

.. autosummary::
    :toctree: modules/auto_generated/

    pairwise_costs


------------------------------------------------------------

.. _datasets_ref:

:mod:`ddop.datasets`: Datasets
==============================

``ddop`` comes with a few default datasets that can be loaded using the ``ddop.datasets`` module.


.. automodule:: ddop.datasets
    :no-members:
    :no-inherited-members:

Loaders
-----------

.. currentmodule:: ddop.datasets

.. autosummary::
    :toctree: modules/auto_generated/

    load_yaz
    load_bakery
    load_SID

These datasets are useful to quickly illustrate the behavior of the various algorithms implemented in ddop.