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.
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:
library("animovement")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:
- Introduction to
animovement - Read trackball data
- Clean tracks
- Calculate kinematics
- Calculate summary statistics
Warning
🏗️ The package is currently in early development and the interface is subject to change. Feel free to play around and provide feedback.
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!
To cite animovement in publications use:
citation("animovement")
#> To cite package 'animovement' in publications use:
#>
#> Roald-Arbøl M (2025). "animovement: An R toolbox for analysing animal
#> movement across space and time."
#> <http://www.roald-arboel.com/animovement/>.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Misc{roaldarbol:2025,
#> title = {animovement: An R toolbox for analysing animal movement across space and time.},
#> author = {Mikkel Roald-Arbøl},
#> year = {2025},
#> url = {http://www.roald-arboel.com/animovement/},
#> abstract = {An R toolbox for analysing animal movement across space and time.},
#> version = {0.6.0},
#> }