Traja: A Python toolbox for animal trajectory analysis
Justin Shenk, Wolf Byttner, Saranraj Nambusubramaniyan, Alexander Zoeller
Abstract
There are generally four categories of trajectory data: mobility of people, mobility of transportation vehicles, mobility of animals, and mobility of natural phenomena Animal tracking is important for fields as diverse as ethology, optimal foraging theory, and neuroscience. Mouse behavior, for example, is a widely studied in biomedical and brain research in models of neurological disease such as stroke. 1 Several tools exist which allow analyzing mouse locomotion. Tools such as Ethovision DLCAnalyzer 2 provides a collection of R scripts for analyzing positional data, in particular visualizing, classifying and plotting movement. B-SOiD (Hsu & Yttri, 2020) allows unsupervised clustering of behaviors, extracted from the pose coordinate outputs of DeepLabCut. SimBA (sgoldenlab et al., 2021) provides several classifiers and tools for behavioral analysis in video streams in a Windowsbased graphical user interface (GUI) application.