Skip to content

Latest commit

 

History

History
64 lines (45 loc) · 4.55 KB

README.md

File metadata and controls

64 lines (45 loc) · 4.55 KB
Raw

CRAN Build Status codecov codecov License: MIT DOI fair-software.eu Downloads

waydown

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

Getting started

Prerequisites

This is an R package. R is required, RStudio is recommended.

Installing

Latest stable version

This package can be installed from CRAN. Type install.packages("waydown") in your R command console.

Latest version

Type devtools::install_github("PabRod/waydown", ref = "develop") in your R command console.

Reproduce my manuscript

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:

  1. Type devtools::install_github("PabRod/waydown", ref = "feature/reproducible") to install waydown and the libraries needed to reproduce the manuscript
  2. Clone or download the reproducible branch of this repository (shortcut: git clone --single-branch --branch feature/reproducible https://github.com/PabRod/waydown.git)
  3. knit the file vignettes\manuscript.Rmd

Rendering the figures requires Python, and the packages matplotlib and numpy.

Running the tests

The integrity of this package can be checked by running the battery of tests available at ./tests.

Examples of usage

A vignette with examples of usage can be found in inst/doc/examples.pdf

Citation

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

Authors

License

This project is licensed under the MIT License.

Acknowledgements

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.