README.org

* Description
Code (Version =1.1.1=) utilized to generate the results in the publication "Prosumer Response Estimation using SINDyc in conjunction with Markov-chain Monte-Carlo Sampling":

#+BEGIN_QUOTE
Banis, F.; Madsen, H.; Poulsen, N.K.; Guericke, D. Prosumer Response Estimation Using SINDyc in Conjunction with Markov-Chain Monte-Carlo Sampling. Energies 2020, 13, 3183.
#+END_QUOTE

This code is citable through the following BibTeX entry:

#+BEGIN_QUOTE
@software{banis_frederik_2020_3911952,
  author       = {Banis, Frederik},
  title        = {SINDyc And MCMC Framework},
  month        = jun,
  year         = 2020,
  publisher    = {Zenodo},
  version      = {1.1.1},
  doi          = {10.5281/zenodo.3911952},
  url          = {https://doi.org/10.5281/zenodo.3911952}
}
#+END_QUOTE

See https://zenodo.org/record/3911952#.XvmavjWxWCh.
* Prerequisites
- Tested on a UNIX-based system.
- python :: Tested with version =3.7.7=.
  - numpy :: https://pypi.org/project/numpy/. Tested with version =1.18.5=.
  - pandas :: https://pypi.org/project/pandas/. Tested with version =1.0.5=.
  - control :: https://pypi.org/project/control/. Tested with version =0.8.2=.
  - pystan :: https://pypi.org/project/pystan/. Tested with version =2.19.1.1=.
  - pySINDy :: https://github.com/luckystarufo/pySINDy/.
    - Recent package version, untested :: https://github.com/dynamicslab/.
* Installation
- Install python and =pip= for your system and install the packages listed in the previous Section [[Prerequisites]] via =pip=.
- Create the =Illustrations= and =Data= folders in this directory, if not already present. Plots and data will be saved in this directory, respectively.
* License
This code is licensed under the MIT license. See the =License= statement in this directory.
* Miscellaneous
Formatted using =black= (https://pypi.org/project/black/). Versioned using =semver= (https://semver.org/).