pyeee: Parameter screening using Efficient/Sequential Elementary Effects, an extension of Morris' method
Creators
- 1. Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement - INRAE, Nancy, France
- 2. University of Waterloo, ON, Canada
Description
pyeee is a Python library for performing parameter screening of computational models. It uses Efficient or Sequential Elementary Effects, an extension of Morris' method of Elementary Effects, published by:
Cuntz M, Mai J, Zink M, Thober S, Kumar R, Schäfer D, Schrön M, Craven J, Rakovec O, Spieler D, Prykhodko V, Dalmasso G, Musuuza J, Langenberg B, Attinger A, and Samaniego L (2015) Computationally inexpensive identification of noninformative model parameters by sequential screening, Water Resources Research 51, 6417-6441, doi:10.1002/2015WR016907
pyeee can be used with Python functions as well as external executables using libraries such as partialwrap. Function evaluations can be distributed with Python's multiprocessing or via MPI.
The complete documentation of pyeee is available at: https://mcuntz.github.io/pyeee/
A similar package (EEE) using a combination of bash and Python scripts is presented at: https://doi.org/10.5281/zenodo.3620894
The version 4.0 modernised code structure and documentation, moving everything to Github, and version 4.1 added pyeee to conda-forge.
Files
mcuntz/pyeee-4.1.12.zip
Files
(1.8 MB)
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Additional details
Related works
- Is derived from
- Software: https://github.com/mcuntz/pyeee/ (URL)
- Is documented by
- Software documentation: https://mcuntz.github.io/pyeee/ (URL)
- Is identical to
- Software: https://pypi.org/project/pyeee/ (URL)
- Software: https://anaconda.org/conda-forge/pyeee/ (URL)
- Is published in
- Journal: 10.1002/2015WR016907 (DOI)