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• Documentation <https://chaospy.readthedocs.io/en/master>_
• Interactive tutorials with Binder <https://mybinder.org/v2/gh/jonathf/chaospy/master?filepath=docs%2Fuser_guide>_
• Code of conduct <https://github.com/jonathf/chaospy/blob/master/CODE_OF_CONDUCT.md>_
• Contribution guideline <https://github.com/jonathf/chaospy/blob/master/CONTRIBUTING.md>_
• Changelog <https://github.com/jonathf/chaospy/blob/master/CHANGELOG.md>_
• License <https://github.com/jonathf/chaospy/blob/master/LICENCE.txt>_

Chaospy is a numerical toolbox for performing uncertainty quantification using polynomial chaos expansions, advanced Monte Carlo methods implemented in Python. It also include a full suite of tools for doing low-discrepancy sampling, quadrature creation, polynomial manipulations, and a lot more.

The philosophy behind chaospy is not to be a single tool that solves every uncertainty quantification problem, but instead be a specific tools to aid to let the user solve problems themselves. This includes both well established problems, but also to be a foundry for experimenting with new problems, that are not so well established. To do this, emphasis is put on the following:

• Focus on an easy to use interface that embraces the pythonic code style <https://docs.python-guide.org/writing/style/>_.
• Make sure the code is "composable", such a way that changing one part of the code with something user defined should be easy and encouraged.
• Try to support a broad width of the various methods for doing uncertainty quantification where that makes sense to involve chaospy.
• Make sure that chaospy plays nice with a large set of of other other similar projects. This includes numpy <https://numpy.org/>, scipy <https://scipy.org/>, scikit-learn <https://scikit-learn.org>, statsmodels <https://statsmodels.org/>, openturns <https://openturns.org/>, and gstools <https://geostat-framework.org/> to mention a few.
• Contribute all code to the community open source.

Installation

Installation should be straight forward from pip <https://pypi.org/>_:

.. code-block:: bash

pip install chaospy

Or if Conda <https://conda.io/>_ is more to your liking:

.. code-block:: bash

conda install -c conda-forge chaospy

Then go over to the documentation <https://chaospy.readthedocs.io/en/master>_ to see how to use the toolbox.

Development

Installing chaospy and its dependencies in developer mode is done as follows:

.. code-block:: bash

pip install -r requirements-dev.txt
pip install -e .

Testing

To ensure that the code run on your local system, run the following:

.. code-block:: bash

pytest --doctest-modules chaospy/ tests/ README.rst

Documentation

The documentation build assumes that pandoc is installed on your system and available in your path.

To build documentation locally on your system, use make from the docs/ folder:

.. code-block:: bash

cd docs/
make html

Run make without argument to get a list of build targets. The HTML target stores output to the folder doc/.build/html.