Introduction

SGMethods is a Python object-oriented code for sparse grid interpolation (also called stochastic collocation) with a focus on parametric coefficient PDEs.

Features of SGMethods

  • Several nodes, multi-index sets, and interpolation methods are implemented…

  • Or you can define and use your own following the examples

  • Single- and multilevel methods

  • A-priori and adaptive sparse grid construction (Coming soon)

  • Tests wit pytest

  • Documentation in sphinx

Installation

For the moment, only the repository is available. In the future a package will be released on PyPI.

  1. Clone the repository:

    git clone git@github.com:andreascaglioni/SGMethods.git

or:

git clone https://github.com/andreascaglioni/SGMethods.git

  1. Install the dependencies:

    pip install -r requirements.txt

  2. Run the tests from the root directory:

    pytest tests/test_*.py

Usage

See the Tutorials for examples on how to use the code.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Andrea Scaglioni - Get in touch on my website <https://andreascaglioni.net/contacts>

From README.md on GitHub .