GeoPressureTemplate

Analyzing geolocator data with GeoPressureR is full of potential, but the the path is long and the journey can be challenging. GeoPressureTemplate provides a start-up R project to make that journey easier.

This Github repository template contains a standard project folder structure and R script to store your data, analyse it, and produce outputs.

⚠️ To use this template, you must be familiar with the full GeoPressureR workflow, described in the GeoPressureManual.

📁 Project structure

We defined a standardized project folder structure based on a mix of rrrpkg, rrtools and cookiecutter data science.

GeoPressureTemplate/
├── DESCRIPTION                             # Project metadata and dependencies
├── README.md                               # Top-level description of content and guide to users
├── GeoPressureTemplate.Rproj               # R project file
├── LICENCES.md                             # Conditions of re/use the data and code
├── config.yml                              # YML file used to defined the parameters used in the analysis
├── data/                                 
│   ├── raw_tag/                            # Raw geolocator data (do not modify!)
│   │   ├── 18LX/
│   │   │   ├── 18LX_20180725.acceleration
│   │   │   ├── 18LX_20180725.glf
│   │   │   └── 18LX_20180725.pressure 
│   │   └── CB619/ 
│   │       └── CB619.deg
│   ├── tag_label/                          # Trainset csv file generated with analyis/1-label.qmd
│   │   ├── 18LX-labeled.csv
│   │   ├── 18LX.csv 
│   │   ├── CB619-labeled.csv
│   │   └── CB619.csv            
│   ├── twilight_label/                     # Trainset csv file generated with analyis/2-twilight.qmd
│   │   ├── 18LX-labeled.csv
│   │   └── 18LX.csv
│   ├── wind/                               # ERA-5 wind data generated with analyis/3-wind.qmd
│   │   └── 18LX/
│   │       ├── 18LX_1.nc
│   │       └── ...
│   └── interim/                            # Intermediate data, typically .RData or .Rds
│       └── 18LX.RData                      
├── analysis/                               # R code used to analyse your data.
│   ├── 1-label.qmd
│   ├── 2-twilight.qmd
│   ├── 3-wind.qmd
│   ├── 4-geopressure.R
└── output/   
    ├── create_figures.R
    └── figures/

💡 Get started

🛠️ Create your project

Option 1: with a Github repository (recommended)

Create your project repo by clicking on the green button "Use this template".
Choose a project name (e.g., my_tracking_study_name) specific to your research. Note that this will become the name of your folder on your computer too.
Clone the repository on your computer.
Done! 🎉

Option 2: without a Github repository

Download the repo by clicking on the green button Code and Download ZIP
Unzip and rename the folder name to your own project name.
Done! 🎉

🏠 Make yourself at home

Rename GeoPressureTemplate.Rproj to your study name (e.g., my_tracking_study_name.Rproj). You can now open the project on RStudio.
Edit the DESCRIPTION file (see https://r-pkgs.org/description.html for details).
Delete the content of README.md and write your research objectives, describing your basic data, method etc.
Replace the content of data/ with your tag data.
Install the dependencies needed with

devtools::install()

Optionally, modify the LICENCES.md file (see https://r-pkgs.org/license.html for details).

What is the `config.yml` file?

Before jumping into the analysis, we need to introduce config.yml. It's a YAML file which defines the parameters used in the analysis. Separating these parameters from the main code follows best practices in terms of reproducibility, readability, and sharability. We use the config R package to retrieve the parameter values in the code with,

config::get("crop_start", config = "18LX") # "2017-06-20"

One advantage of this file is the ability to define a default set of parameters (i.e. valid for all tags), as well as specific parameters for each tag.

config::get("thr_gs", config = "18LX") # 150

📈 Analyse the data

Now that you are set up, it's time to get serious 😬

Step 1: Preparation

In this first step, we will make sure everything is ready to run the model. This involves setting up the parameters in config.yml while running the following three scripts:

Run 1-label.qmd
(optional) 2-twilight.qmd
(optional) 3-wind.qmd

While doing so, please keep in mind: - Nothing is saved at the end of the script (and that's how it's supposed to be!). Only label files and config.yml should be edited. - The scripts should be run successively for each tag separately - We use quarto script to make it easy to run chunks based on your needs (e.g., re-run a small chunk after making a change). The scripts are not meant to be run with "Run all". - These scripts should be adapted based on your project, but the same script should run for all your tags.

Step 2: Compute the trajectory

The main script is 4-geopressure.R

Step 3: Your own analyis

Publication

For peer-review publication, it is essential that the data and code are accessible to reviewer. Because inaccurate labeling can lead to wrong trajectory, we highly encourage you to publish your data and code on Zenodo. This is made very easy using this github repository and this guide. This process will generate a DOI for your data and code which can be used in your repository. Here is an ey (e.g., https://zenodo.org/record/7471405)

What it needs to include:

🔗 Advanced options

Generate a citation file with usethis::use_citation() and cffr.
Use renv to make your work reproducible.

Rafnuss/GeoPressureTemplate