do_pca

This function runs a PCA to place events on collective motion into less-dimentional space.

internal

Provides a pipeline for the comparative analysis of
collective movement data (e.g. fish schools, bird flocks, baboon troops) by
processing 2-dimensional positional data (x,y,t) from GPS trackers or computer
vision tracking systems, discretizing events of collective motion, calculating
a set of established metrics that characterize each event, and placing the
events in a multi-dimensional swarm space constructed from these metrics.
The swarm space concept, the metrics and data sets included are described in:
Papadopoulou Marina, Furtbauer Ines, O'Bryan Lisa R., Garnier Simon,
Georgopoulou Dimitra G., Bracken Anna M., Christensen Charlotte and King
Andrew J. (2023) <doi:10.1098/rstb.2022.0068>.

Marina Papadopoulou

swaRmverse

Swarm Space Creation

Simon Garnier

do_pca function

<dl><dt>df</dt>
<dd>A dataframe with the metrics of collective motion
per event.</dd></dl>

Arguments

Marina Papadopoulou <a href="/link/m.papadopoulou.rug%40gmail.com?package=swaRmverse&version=0.1.1" data-mini-rdoc="swaRmverse::m.papadopoulou.rug@gmail.com">m.papadopoulou.rug@gmail.com</a>

Author

Perform PCA — do_pca

<dl>

<dt>df</dt>
<dd>A dataframe with the metrics of collective motion
per event.</dd>

</dl>

Marina Papadopoulou <a href='mailto:m.papadopoulou.rug@gmail.com'>m.papadopoulou.rug@gmail.com</a>

do_pca: Perform PCA

Description

Usage

Value

Arguments

Author