chaospy 4.3.18
pip install chaospy
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Numerical tool for performing uncertainty quantification
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- License: MIT License (MIT license)
- Requires: Python >=3.7
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Project description
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:
pip install chaospy
Alternatively, if you prefer Conda:
conda install -c conda-forge chaospy
After installation, visit the documentation to learn how to use the toolbox.
Development
To install chaospy and its dependencies in developer mode:
pip install -e .[dev]
Testing
To run tests on your local system:
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:
cd docs/
make html
Run make without arguments to view other build targets. The HTML documentation will be output to doc/.build/html.
Project details
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- License: MIT License (MIT license)
- Requires: Python >=3.7
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Provides-Extra:
dev
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