An R toolbox for analysing movement across space and time
The primary aim of the animovement package is to provide a unified, standardised workflow for analysing movement data in a tidyverse-friendly syntax.
We work actively with the developers of the Python movement package, to reach a similar data standards, workflow and use cases; if you prefer analysing your data in Python, we highly recommend using movement.
Installation
You can install the development version of animovement with:
install.packages('animovement', repos = c('https://animovement.r-universe.dev', 'https://cloud.r-project.org'))Once you have installed the package, you can load it with:
Documentation
Analysis of animal movement follows a similar workflow irrespective of the type of data (e.g. pose estimation, centroid tracking, trackball, treadmill). See our docs to go through the steps, one-by-one:
Status
Warning
🏗️ The package is currently in early development and the interface is subject to change. Feel free to play around and provide feedback.
Contribute
If your favourite type of movement data is not currently supported, we would love to get a sample of your data to support it!
If you enjoy the package, please make sure to cite it. If you find a bug, feel free to open an issue!
Citation
To cite animovement in publications use:
citation("animovement")
#> To cite package 'animovement' in publications use:
#>
#> https://animovement.dev/animovement/
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Misc{roaldarbol:2025,
#> title = {animovement: An R toolbox for analysing movement across space and time.},
#> author = {Mikkel Roald-Arbøl},
#> year = {2025},
#> url = {http://animovement.dev/},
#> abstract = {An R toolbox for analysing movement across space and time.},
#> version = {0.7.0},
#> }