SGMethods

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

Table of Contents

• Features
• Installation
• Usage
• Contributing
• License

Features

• Several nodes, multi-index sets, and interpolation methods are implemented...
• Or you can define and use your own following the examples;
• Data structures to efficiently handle high-dimensional functions and objects;
• Single- and multilevel scheme;
• A-priori and adaptive sparse grid construction (Coming soon);
• Thorough testing and documentation.

Installation

1. Clone the repository

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

or

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

2. Install the dependencies

pip install -r requirements.txt

3. Run the tests (from the project root directory):

pytest tests/test_*.py

Usage

See the examples in the omonymous directory.

Read the documentation at: https://andreascaglioni.github.io/SGMethods/

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