nilomr/birdsong-demography

Code to reproduce the results in a paper on demographic drivers of cultural dynamics

Table of Contents

• Table of Contents
• This Repository
  • Project Organization
• Getting Started
  • Installation
  • Dependencies
• Running the analyses
  • Models
  • Figures and model output
• Bugs and Issues

This Repository

This repository includes the following main features,

• An RStudio project birdsong-demography.Rproj
• Package dependency management using renv
• Configuration using config
• A scripts directory with the code necessary to reproduce the analysis and figures in this paper.
• A R folder for R source code and reusable functions

and uses the output of other dedicated repositories:

• Wytham Great Tit Song Dataset
• Song Type Validation

Project Organization

...
├── data
│   ├── derived v                derived data, created by scripts
│   ├── fits                       model fits (brms .rds objects)
│   └── raw                         original data, never modified
├── output
│   └── figures
├── R                                          reusable functions
│   ├── io.R
│   ├── rplot.R
│   └── utils.R
├── renv 
├── scripts                        code to reproduce the analysis
│   ├── maps
│   ├── models
│   │   ├── fit
│   │   ├── plot
│   │   └── report
│   └── plots                extra plots (supplementary material)
├── scripts
│   ├── setup
│   └── pipeline.sh
...
├── .Rprofile                             main configuration file
├── config.yml                                 configuration file
├── dependencies.R                               IDE dependencies
├── LICENSE.md
├── README.md
├── renv.lock                     lockfile detailing dependencies
└── birdsong-demography.Rproj                RStudio project file

Getting Started

Installation

Clone this repository to your local computer using the following command in the terminal:

git clone https://github.com/nilomr/birdsong-demography.git

Then, download the data from OSF, replacing the data folder in the repository with the downloaded data folder¹.

Dependencies

This project uses R v4.2. You must have the renv package installed on your local computer. While in an active session, simply run the following line of code in the R Console.

install.packages('renv')

To install the necessary libraries using renv, run the following line of code in the R Console:

renv::restore()

Depending on your system, this may take a while, and you will likely be prompted (as in installation will just fail) to install some system dependencies.

Running the analyses

Models

Running the script that prepares the derived datasets is not necessary: you already downloaded the derived data from OSF

If you do want to do this to make sure things work correctly, just cd into the ./scripts folder and run bash pipeline.sh in the terminal.

Similarly, the model fits are already in the data, so they will not refit automatically. If you want to refit them, change file_refit = "never" to file_refit = "always" in the relevant function calls.

Figures and model output

Any scripts outside of the ./scripts/setup and ./scripts/models/fit folders can be run independently. Where there is an order constraint, this is indicated in the script name.

Bugs and Issues

If you encounter any bugs or issues, please open an issue. If possible, include a minimal reproducible example and/or screenshots to illustrate the problem.

_{© Nilo M. Recalde, 2023}

Footnotes

1. Data are under version control here, but obtaining these requires git-lfs to be installed on your computer and I can't guarantee that it will work. ↩