llnl-thicket 2023.3.0

Toolkit for exploratory data analysis of ensemble performance data

Thicket

Thicket

A Python-based toolkit for analyzing ensemble performance data. You can find detailed documentation, along with tutorials of Thicket in the ReadtheDocs.

Installation

To use thicket, install it with pip:

$ pip install llnl-thicket

Or, if you want to develop with this repo directly, run the install script from the root directory, which will build the package and add the cloned directory to your PYTHONPATH:

$ source install.sh

Contact Us

You can direct any feature requests or questions to the Lawrence Livermore National Lab's Thicket development team by emailing either Stephanie Brink ([e-mail]) or Olga Pearce ([e-mail]).

Contributing

Thicket is an open-source project. We welcome contributions via pull requests, and questions, feature requests, or bug reports via issues.

License

Thicket is distributed under the terms of the MIT license.

All contributions must be made under the MIT license. Copyrights in the Thicket project are retained by contributors. No copyright assignment is required to contribute to Thicket.

See LICENSE and NOTICE for details.

SPDX-License-Identifier: MIT

LLNL-CODE-834749