How to add code coverage (codecov) to your R package?

During the development of another R package I wasted a bit of time figuring out how to add code coverage to my package. I had the same problem last time so I decided to write up the procedure step-by-step.

Provided that you’ve already written an R package, the next step is to create tests. Luckily, devtools package makes setting up both testing and code coverage a breeze.

Let’s start with adding an infrastructure for tests with devtools:

Then add a test file of your_function() to your tests folder:

Then add the scaffolding for the code coverage (codecov)
use_coverage(pkg = ".", type = c("codecov"))

After running this code you will get a code that can be added to your README file to display a codecov badge. In my case it’s the following:
[![Coverage Status](](

This will create a codecov.yml file that needs to be edited by adding:
comment: false
language: R
sudo: false
cache: packages
- Rscript -e 'covr::codecov()'

Now log in to using the GitHub account. Give codecov access to the project where you want to cover the code. This should create a screen where you can see a token which needs to be copied:

Once this is completed, go back to R and run the following commands to use covr:

codecov(token = "YOUR_TOKEN_GOES_HERE")

The last line will connect your package to codecov. If the whole process worked, you should be able to see a percentage of coverage in your badge, like this:

Click on it to see which functions are not fully covered/need more test:

I hope this will be useful and will save a lot of frustrations.

Interactive plot of fNIRS data

The easiest way to plot ETG-4000 data in R is by using plot_ETG4000() from fnirsr package. However, if you want to explore your data in more detail, then an interactive plot is more appropriate.

I used dygraphs package to create the chart below. In case of using many channels, the colours in the legend can get a bit mixed up like in my example. I haven’t figured out yet how to add a custom colour palette that could deal with multiple channels.

One way or another, this code snippet should be enough to start generating interactive charts. I haven’t added the interactive chart to the main plotting function (i.e. plot_ETG4000) but I might do it in future releases.

The code used to generate the chart is here:

PS: The dygraph generated correctly in the interactive window, when using R notebooks, and when knitting. When I Saved as Web Page from RStudio, I got a header error that I had to clean by removing a tag (<!DOCTYPE html>) from the generated html file.