vlachosgroup/ckbit repository overview

⁠Chemical Kinetic Bayesian Inference Toolbox (CKBIT)

The Chemical Kinetic Bayesian Inference Toolbox (CKBIT) is a Python library for applying Bayesian inference to kinetic rate parameters developed by the Vlachos Research Group at the University of Delaware.

⁠Documentation

Documentation can be found at this webiste: https://vlachosgroup.github.io/ckbit/⁠

⁠Examples

There are examples of the code in the Github examples folder. The examples are provided in both Python scripts and in Jupyter notebooks. Ensure the accompanying Excel files are used as templates for data entry.

⁠Developers

Max Cohen ([email protected]⁠)

⁠License

This project is licensed under the MIT License - MIT License

Copyright (c) 2020 Vlachos Research Group

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

⁠Contributing and Questions

If you have a suggestion, find a bug, or have a question, please post to our Issues page on the Github.

⁠Funding

We acknowledge support by the RAPID manufacturing institute, supported by the Department of Energy (DOE) Advanced Manufacturing Office (AMO), award number DE-EE0007888-9.5. RAPID projects at the University of Delaware are also made possible in part by funding provided by the State of Delaware. The Delaware Energy Institute gratefully acknowledges the support and partnership of the State of Delaware in furthering the essential scientific research being conducted through the RAPID projects.

⁠Special Thanks

• Dr. Jonathan Lym
• Dr. Jeffrey Frey