Computation of approximate potentials for both gradient and non
gradient fields. It is known from physics that only gradient fields, also
known as conservative, have a well defined potential function. Here we
present an algorithm, based on the classical Helmholtz decomposition, to
obtain an approximate potential function for non gradient fields.
More information in
Rodríguez-Sánchez (2020)

This package implements some methods for computing potential landscapes for non-gradient systems.
For a detailed overview of the underlying ideas, please refer to:
Rodríguez-Sánchez P
, van Nes EH, Scheffer M (2020) Climbing Escher’s stairs: A way to approximate stability landscapes in multidimensional systems. PLOS Computational Biology 16(4): e1007788. https://doi.org/10.1371/journal.pcbi.1007788
This is an R package. R is required, RStudio is recommended.
Type devtools::install_github("PabRod/waydown", ref = "master") in your R command console.
Type devtools::install_github("PabRod/waydown", ref = "develop") in your R command console.
If you want to locally reproduce my manuscript Climbing Escher's stairs: a simple quasi-potential algorithm for weakly non-gradient systems, follow these steps:
devtools::install_github("PabRod/waydown", ref = "feature/reproducible") to install waydown and the libraries needed to reproduce the manuscriptgit clone --single-branch --branch feature/reproducible https://github.com/PabRod/waydown.git)vignettes\manuscript.RmdRendering the figures requires Python, and the packages matplotlib and numpy.
The integrity of this package can be checked by running the battery of tests available at ./tests.
A vignette with examples of usage can be found in inst/doc/examples.pdf
If you use this software, the information below may help you citing it.
Rodríguez-Sánchez, P. (2019). PabRod/waydown: a package for computing pseudopotentials. https://doi.org/10.5281/zenodo.2591550
If you want to cite also the paper describing the algorithm used by this software, please use:
Rodríguez-Sánchez, P., van Nes, E. H., & Scheffer, M. (2020). Climbing Escher’s stairs: A way to approximate stability landscapes in multidimensional systems. PLOS Computational Biology, 16(4), e1007788. https://doi.org/10.1371/journal.pcbi.1007788
This project is licensed under the MIT License.
This work was greatly inspired by the dicussions with Cristina Sargent, Iñaki Úcar, Enrique Benito, Tobias Oertel-Jäger, Jelle Lever, Sanne J.P. van den Berg and Els Weinans. This work was supported by funding from the European Union's Horizon 2020 research and innovation programme for the ITN CRITICS under Grant Agreement Number 643073.