meerkat-behaviour-classifier-inator

This repo contains code for predicting meerkat behaviour from accelerometer data. The raw data used here was obtained as part of the CCAS project. This project is described in detail in our upcoming pre-print and in our upcoming paper. The members who contributed to the code in this repo are:

• Pranav Minasandra
• Amlan Nayak
• Ariana Strandburg-Peshkin

The folks who worked on this project directly at other parts, including but not limited to fieldwork, data preprocessing, etc. include:

• Lily Johnson-Ulrich
• Vlad Demartsev
• Marta Manser

Installation and setup

On Linux and mac, the following command will setup the folder structure and download and setup code.

curl -sSf https://raw.githubusercontent.com/pminasandra/meerkat-acc/master/setup.sh | bash

This software was written to analyse meerkat accelerometry data from collared meerkats. It constructs an elegant machine learning system using pre-recorded ground truth data, and provides a second-by-second report of the behavioural states of the hyenas. This software, and all libraries used by it, are open source.

Details on folder structure

The following folder structure is recommended (and will be setup by the command above).

<PROJECTROOT>/ (usually autonamed meerkat-acc by the command above)
|
|-- classifier/
|-- Data/
|-- Figures/

Generally, PROJECTROOT can be any folder of your choosing. In the classifier subfolder, you a file named .cw that contains only the filepath for PROJECTROOT (also done by the command above).

Dependencies

The following software components need to be installed. These will not be installed by the command above, please use the below instructions. Commands mentioned work in typical Linux systems running the bash shell (e.g., Ubuntu or Pop!_OS). If you are using Windows or Mac, please install things using the appropriate way for your system.

Basic software

Python 3.8+. We have tested on Python 3.10. To install, use

sudo apt install python3

Python libraries

The following python libraries are needed.

• numpy
• scipy
• matplotlib
• pandas
• scikit-learn

To install, you can use

python3 -m pip install --user numpy scipy matplotlib pandas scikit-learn

Usage

• Copy the folders ACC_GPS and Audits (made available here soon) into the Data folder in your PROJECTROOT.
• Run python3 main.py to run all analyses in order.

Contact

If you have any questions or problems with the code, please feel free to contact me using the methods mentioned on my website. If your question is related explicitly to the code, mentioning the make and build of your OS, and a detailed log of your error, would be very helpful. Have fun with your analyses!