Continuous integration is an amazing tool when developing R packages. We push a change to the server, and a process is spawned that checks we haven’t done something silly. It protects us from ourselves! However this process can become slow, as typically the CI process starts with a blank virtual machine (VM). If you are
In our recent post about saving R graphics, it became obvious that achieving consistent graphics across platforms or even saving the “correct” graph on a particular OS was challenging. Getting consistent fonts across platforms often failed, and for the default PNG device under Windows, anti-aliasing was also an issue. The conclusion of the post was
R is known for it’s amazing graphics. Not only ggplot2, but also plotly, and the other dozens of packages at the graphics task view. There seems to be a graph for every scenario. However once you’ve created your figure, how do you export it? This post compares standard methods for exporting R plots as PNGs/PDFs
SatRdays SatRdays are great. Low cost R events, held around the world. What’s not to love! For the last year, we have been offering automatic sponsorship for all SatRday events. All the organisers have to do is complete a quick questionnaire and the money is sent on it’s way. So far we have sponsored seven
Before we start anything, I’d like to mention that most of the hard work came from nsaunders and his great blog post Idle thoughts lead to R internals: how to count function arguments. Let’s get started. The aim of this blog is to capture the number of arguments present in each function with packages of
You’ll be pleased to know that Jumping rivers are running R training courses up and down the UK, in London, Newcastle, Belfast and Edinburgh. I’ve put together a quick summary of the courses available through til the end of the year. They are sorted by place then date. You can find the booking links and
This blog post has two goals Investigate the bench package for timing R functions Consequently explore the different algorithms in the digest package using bench What is digest? The digest package provides a hash function to summarise R objects. Standard hashes are available, such as md5, crc32, sha-1, and sha-256. The key function in the
One of the great things about R, is the myriad of packages. Packages are typically installed via CRAN Bioconductor GitHub But how often do we think about what we are installing? Do we pay attention or just install when something looks neat? Do we think about security or just take it that everything is secure?