An all-in-one tool for fitting kinetic models using spectral and other state data
Reason this release was yanked:
Bugs
Project description
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
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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
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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.
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