chaospy

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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 designed for performing uncertainty quantification through polynomial chaos expansions and advanced Monte Carlo methods implemented in Python. It includes a comprehensive suite of tools for low-discrepancy sampling, quadrature creation, polynomial manipulations, and much more.

The philosophy behind chaospy is not to serve as a single solution for all uncertainty quantification challenges, but rather to provide specific tools that empower users to solve problems themselves. This approach accommodates well-established problems but also serves as a foundry for experimenting with new, emerging problems. Emphasis is placed on the following:

• Focus on an easy-to-use interface that embraces the pythonic code style <https://docs.python-guide.org/writing/style/>.
• Ensure the code is “composable,” meaning it’s designed so that users can easily and effectively modify parts of the code with their own solutions.
• Strive to support a broad range of methods for uncertainty quantification where it makes sense to use chaospy.
• Ensure that chaospy integrates well with a wide array of other projects, including 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/>, among others.
• Contribute all code as open source to the community.

Installation

Installation is straightforward via pip <https://pypi.org/>_:

… code-block:: bash

pip install chaospy

Alternatively, if you prefer Conda <https://conda.io/>_:

… code-block:: bash

conda install -c conda-forge chaospy

After installation, visit the documentation <https://chaospy.readthedocs.io/en/master>_ to learn how to use the toolbox.

Development

To install chaospy and its dependencies in developer mode:

… code-block:: bash

pip install -e .[dev]

Testing

To run tests on your local system:

… code-block:: bash

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

Documentation

Ensure that pandoc is installed and available in your path to build the documentation.

From the docs/ directory, build the documentation locally using:

… code-block:: bash

cd docs/
make html

Run make without arguments to view other build targets. The HTML documentation will be output to doc/.build/html.