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https://github.com/robinthibaut/skbel

SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
https://github.com/robinthibaut/skbel

bayesian-inference gaussian-process gaussian-process-regression gaussian-processes geology groundwater hydrogeology machine-learning multiple-output-regression multivariate-regression pfa sklearn

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SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.

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README 

        
.. -*- mode: rst -*-



|Travis|_  |Doc|_ |Black|_ |PythonVersion|_ |PyPi|_ |DOI|_ |Downloads|_



.. |Travis| image:: https://travis-ci.com/robinthibaut/skbel.svg?branch=master

.. _Travis: https://travis-ci.com/robinthibaut/skbel



.. |Doc| image:: https://readthedocs.org/projects/skbel/badge/?version=latest

.. _Doc: https://skbel.readthedocs.io/en/latest/?badge=latest



.. |CodeCov| image:: https://codecov.io/gh/robinthibaut/skbel/branch/main/graph/badge.svg?token=S0T9NW3VK6

.. _CodeCov: https://codecov.io/gh/robinthibaut/skbel



.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/skbel

.. _PythonVersion: https://img.shields.io/pypi/pyversions/skbel



.. |PyPi| image:: https://badge.fury.io/py/skbel.svg

.. _PyPi: https://badge.fury.io/py/skbel



.. |Black| image:: https://img.shields.io/badge/code%20style-black-000000.svg

.. _Black: https://github.com/psf/black



.. |DOI| image:: https://zenodo.org/badge/369214956.svg

.. _DOI: https://zenodo.org/badge/latestdoi/369214956



.. |Downloads| image:: https://pepy.tech/badge/skbel

.. _Downloads: https://pepy.tech/project/skbel



.. |PythonMinVersion| replace:: 3.7

.. |NumPyMinVersion| replace:: 1.14.6

.. |SciPyMinVersion| replace:: 1.1.0

.. |JoblibMinVersion| replace:: 0.11

.. |MatplotlibMinVersion| replace:: 2.2.2

.. |Scikit-ImageMinVersion| replace:: 0.24.1

.. |PandasMinVersion| replace:: 0.25.0

.. |SeabornMinVersion| replace:: 0.9.0

.. |PytestMinVersion| replace:: 5.0.1



.. image:: https://raw.githubusercontent.com/robinthibaut/skbel/master/docs/img/illu-01.png



**skbel** is a Python module for implementing the Bayesian Evidential Learning framework built on top of

scikit-learn and is distributed under the 3-Clause BSD license.



For more information, read the `documentation `_ and run the example `notebook `_.



Installation

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



Dependencies

~~~~~~~~~~~~



skbel requires:



- Python (>= |PythonMinVersion|)

- Scikit-Learn (>= |Scikit-ImageMinVersion|)

- NumPy (>= |NumPyMinVersion|)

- SciPy (>= |SciPyMinVersion|)

- joblib (>= |JoblibMinVersion|)



=======



Skbel plotting capabilities require Matplotlib (>= |MatplotlibMinVersion|).



User installation

~~~~~~~~~~~~~~~~~



The easiest way to install skbel is using ``pip``   ::



    pip install skbel



Development

-----------



We welcome new contributors of all experience levels.



Important links

~~~~~~~~~~~~~~~



- Official source code repo: https://github.com/robinthibaut/skbel/

- Download releases: https://pypi.org/project/skbel/

- Issue tracker: https://github.com/robinthibaut/skbel/issues



Source code

~~~~~~~~~~~



You can check the latest sources with the command::



    git clone https://github.com/robinthibaut/skbel.git



Contributing

~~~~~~~~~~~~



Contributors and feedback from users are welcome. Don't hesitate to submit an issue or a PR, or request a new feature.



Testing

~~~~~~~



After installation, you can launch the test suite from outside the source

directory (you will need to have ``pytest`` >= |PyTestMinVersion| installed)::



    pytest skbel



Help and Support

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



Documentation

~~~~~~~~~~~~~



- HTML documentation (latest release): https://skbel.readthedocs.io/en/latest/



Communication

~~~~~~~~~~~~~



- Github Discussions: https://github.com/robinthibaut/skbel/discussions



How to cite

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



Thibaut, Robin, & Maximilian Ramgraber. (2021). SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn (v2.0.0). Zenodo. https://doi.org/10.5281/zenodo.6205242



BibTeX::



    @software{thibaut_skbel_2021,

    author       = {Thibaut, Robin and Maximilian Ramgraber},

    title        = {{SKBEL} - Bayesian Evidential Learning framework built on top of scikit-learn},

    month        = {9},

    year         = 2021,

    publisher    = {Zenodo},

    version      = {v2.0.0},

    doi          = {10.5281/zenodo.6205242},

    url          = {https://doi.org/10.5281/zenodo.6205242},

    }



Notebooks and tutorials

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



Nolwenn Lesparre, Nicolas Compaire, Thomas Hermans and Robin Thibaut. (2022). 4D Temperature Monitoring with BEL. [Dataset]. Kaggle. doi: 10.34740/kaggle/ds/2275519. url: https://doi.org/10.34740/kaggle/ds/2275519



Thibaut, Robin (2021). WHPA Prediction. [Dataset]. Kaggle. doi:10.34740/kaggle/dsv/2648718. url: https://www.kaggle.com/dsv/2648718



Peer-reviewed publications using SKBEL

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



Thibaut, Robin, Nicolas Compaire, Nolwenn Lesparre, Maximilian Ramgraber, Eric Laloy, and Thomas Hermans (Nov. 2022). “Comparing Well and Geophysical Data for Temperature Monitoring Within a Bayesian Experimental Design Framework”. In: Water Resources Research 58 (11). issn: 0043-1397. doi: 10.1029/2022WR033045. url: https://onlinelibrary.wiley.com/doi/10.1029/2022WR033045.



Thibaut, Robin, Eric Laloy, and Thomas Hermans (Dec. 2021). “A new framework for experimental design using Bayesian Evidential Learning: The case of wellhead protection area”. In: Journal of Hydrology 603, p. 126903. issn: 00221694. doi: 10.1016/j.jhydrol.2021.126903. url: https://linkinghub.elsevier.com/retrieve/pii/S0022169421009537.



Research project

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



Logs and results of the research project are available on the `project page `_.