ARUtools ARUtools website

Codecov test coverage ARUtools status badge Project Status: Active – The project has reached a stable, usable state and is being actively developed. R-CMD-check CRAN status

The goal of ARUtools is to facilitate the processing of ARU data and subsampling of recordings. Parse Autonomous Recording Unit (ARU) data and for sub-sampling recordings. Extract Metadata from your recordings, select a subset of recordings for interpretation, and prepare files for processing on the ‘WildTrax’ https://wildtrax.ca/ platform. Read and process metadata from recordings collected using the SongMeter and BAR-LT types of ARUs.

Installation

The easiest way to install ARUtools is with

install.packages("ARUtools")

Development version

You can install the most current version of ARUtools from the R-universe repository.

install.packages("ARUtools",
                 repos = c("https://arutools.r-universe.dev",
                           "https://cran.r-project.org") )

Alternatively you can build and install the package from GitHub with the code below. You will need to have Rtools installed first:

# install.packages("pak") # Uncomment if you don't have remotes installed.
pak::pak("arutools/ARUtools")

Using “remotes”

# install.packages("remotes")
remotes::install_github("arutools/ARUtools")

Learn to use

The easiest way to dig into using the ARUtools package is using the documentation webpage

There currently are six vignettes that will help you get up and running with cleaning ARU metadata

Provide feedback

If you run into problems or have ideas for extensions, please don’t hesitate to submit an issue.

Motivation and limitations

This package initially started its life as a series of scripts to process recordings from multiple large projects around monitoring migratory bird populations in Ontario’s North.

Moving from scripts to package stemmed from following the wise advice from Hadley Wickham:

A good rule of thumb is to consider writing a function whenever you’ve copied and pasted a block of code more than twice (i.e. you now have three copies of the same code).

With multiple projects, each with their own data issues, it became clear that this would either require copy/pasting a lot of code and likely break something or developing a series of functions that could be shared across projects (i.e. a package).

While that initial version of the code was usable by me and only me, if you’re using the package, it is because of the fantastic work of Steffi LaZerte who translated my mess into the user-friendly functions you see today.

However, due to the variable nature of data management, it is possible that ARUtools may not work well for your project. If you run into issues, please do submit an issue.

There are also other good packages that may be of use to you: