Package: kipet
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://kipet2.readthedocs.ioExamples and Tutorials-https://github.com/kwmcbride/kipet_examplesSource code:-https://github.com/salvadorgarciamunoz/kipetBug reports:-https://github.com/salvadorgarciamunoz/kipet/issuesIt has the following functionality:Simulate a reactive system described with DAEsSolve the DAE system with collocation methodsPre-process dataEstimate variances of noise from the model and measurementsEstimate kinetic parameters from spectra or concentration data across 1 or
multiple experiments with different conditionsEstimate confidence intervals of the estimated parametersAble to estimate variances and parameters for problems where there is dosing / inputs into the systemProvide a set of tools for estimability analysisAllows for wavelength selection of most informative wavelengths from a datasetVisualize resultsInstallationThere are many options for installing KIPET.PyPiA packaged version of KIPET can be installed using:pip install kipetIf you run into errors when installing KIPET using pip (such as when installing into a clean virtual environment), try installing the following packages beforehand:pip install Cython numpy six
pip install kipetAnacondaIf you are using Anaconda, KIPET can be installed using:conda install -c kwmcbride kipetThe anaconda packages have the benefit of including pynumero ready to go, which is needed for some of the methods included in KIPET. You will need to compile these on your own if you choose to install KIPET using a different method. See thepynumero readmefor more information. Otherwise, you can also usek_augfor these methods as well.PoetryYou may also install KIPET with poetry:poetry add kipetGitHubAdditionally, KIPET may be installed directly from the repository (for example, if using poetry, simply install the desired branch (#branch) in the following manner):poetry add git+https://github.com/salvadorgarciamunoz/kipet#masterNaturally you can simply clone or download the repository if you wish.cd <installation directory>
git clone https://github.com/salvadorgarciamunoz/kipet.git
cd kipet
python setup.py installIpopt and k_augTo use KIPET to its full potential, you should install Ipopt and k_aug. Ipopt is
a popular solver for non-linear programs and k_aug is a new method to calculate sensitivities
from the KKT matrix. The latter is required if covariances are to be calculated.TODO: add links to the installation of each here.To help ease the installation of these software tools, there are two scripts written for
Linux OS (Debian) for installing Ipopt and k_aug. These are available herehttps://github.com/kwmcbride/Linux-Setup-ScriptsExamples and TutorialsAll of the example problems can be easily downloaded from the examples repository:cd <example directory>
git clone https://github.com/kwmcbride/kipet_examples.gitTo validate your installation, you can now run the test script included with the examples:cd <example directory>/kipet_examples
python run_examples.pyLicenseGPL-3Authors- 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 UniversityPlease citeC. 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.2019.106716M. 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.2020.104012M. 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.