kipet 0.1.531

An all-in-one tool for fitting kinetic models using spectral and other state data

KIPET is a Python package designed to simulate, and estimate parameters from chemical reaction systems through the use of maximum likelihood principles, large-scale nonlinear programming and discretization methods.

• Documentation: - https://kipet.readthedocs.io
• Examples and Tutorials - https://github.com/kwmcbride/kipet_examples
• Source code: - https://github.com/salvadorgarciamunoz/kipet
• Bug reports: - https://github.com/salvadorgarciamunoz/kipet/issues

It has the following functionality:

• Simulate a reactive system described with DAEs
• Solve the DAE system with collocation methods
• Pre-process data
• Estimate variances of noise from the model and measurements
• Estimate kinetic parameters from spectra or concentration data across 1 or multiple experiments with different conditions
• Estimate confidence intervals of the estimated parameters
• Able to estimate variances and parameters for problems where there is dosing / inputs into the system
• Provide a set of tools for estimability analysis
• Allows for wavelength selection of most informative wavelengths from a dataset
• Visualize results

Installation

A packaged version of KIPET can be installed using:

pip install kipet

If you run into errors when installing KIPET using pip, try installing the following packages beforehand:

pip install Cython numpy six
pip install kipet

You may also install KIPET with poetry (this method is recommended):

poetry add kipet

Finally, if you are using Anaconda, KIPET can be installed using:

conda install -c kwmcbride kipet

Additionally, KIPET may be installed directly from the repository (if you want the latest version, simply install the desired branch (#branch)):

poetry add git+http://github.com/salvadorgarciamunoz/kipet#master

Naturally you can simply clone or download the repository.

License

GPL-3

Authors

- Kevin McBride - Carnegie Mellon University
- Kuan-Han Lin - Carnegie Mellon University
- Christina Schenk - Basque Center for Applied Mathematics
- Michael Short - University of Surrey
- Jose Santiago Rodriguez - Purdue University
- David M. Thierry - Carnegie Mellon University
- Salvador García-Muñoz - Eli Lilly
- Lorenz T. Biegler - Carnegie Mellon University

Please cite

• C. Schenk, M. Short, J.S. Rodriguez, D. Thierry, L.T. Biegler, S. García-Muñoz, W. Chen (2020) Introducing KIPET: A novel open-source software package for kinetic parameter estimation from experimental datasets including spectra, Computers & Chemical Engineering, 134, 106716. https://doi.org/10.1016/j.compchemeng.2019.106716

• M. Short, L.T. Biegler, S. García-Muñoz, W. Chen (2020) Estimating variances and kinetic parameters from spectra across multiple datasets using KIPET, Chemometrics and Intelligent Laboratory Systems, https://doi.org/10.1016/j.chemolab.2020.104012

• M. Short, C. Schenk, D. Thierry, J.S. Rodriguez, L.T. Biegler, S. García-Muñoz (2019) KIPET–An Open-Source Kinetic Parameter Estimation Toolkit, Computer Aided Chemical Engineering, 47, 299-304.