I have long admired albums2hear, a Twitter bot that posts albums. You can read a bit more about it here. There was no mastodon equivalent and so I decided to build one. You can follow the bot – currently called Albums Albums Albums (or AlbumsX3) – here. Idea behind the bot The idea is to periodically post an album.

I have a long-running Raspberry Pi camera project to capture images of the view from a window (more details here). A recent post on mastodon, which showed a keogram, encouraged me to take my PiCam images and turn them into art. The finished product This is the finished wall art, printed on canvas. Ready to hang on the wall.

It’s a New Year and so it is time to post the papers I have selected for a module that I teach on (MD9A8, the module formerly known as MD997). Previous selections are grouped here or here. The list serves as a snapshot of interesting papers published in the previous 12 months or so. I hope it is useful to others who are looking for lists of papers to read, for student selections or for anything else.

There are a few one-liners that I use in the shell to do some really nifty stuff. I struggle to quickly find and reuse these and asked for a solution on Mastodon.

2022 was my best year for running to date. In 2021, my goal was to run 2021 km. For 2022, I wanted to see if I could run 2500 km and also to run 50 HM-or-more distance runs. I managed both and ended the year on a total of 2734 km. I also bagged two PBs for half marathon. Of course, if you subscribe to Strava or VeloViewer or whatever, you can get a nice data visualisation of your year in running.

Another post looking at Twitter data in R. It follows this one and this one. I wanted to look again at my tweeting frequency over the 12 years on Twitter, but this time do it in a calendar view. Something like a GitHub commit calendar would be perfect. I have used a library for this in the past.

Another post about my time on Twitter. I will post the code in a separate post so that the R-bloggers don’t syndicate this one, which is about music . In my time on Twitter I occasionally posted about what I was listening to. I did this with a #NowPlaying hashtag. I wanted to preserve these tweets – and they can all be found below.

Please consider this a “supplementary analysis” to my previous post looking at the frequency of tweets from my personal account over the last 12 years. I was curious about what times I was active on Twitter (measured by when I tweeted). Others might be interested in a solution to look at this in R. The code As in the previous post, we need to get the data into R and then make sure we have a date object to work with.

At the time of writing, I have essentially left Twitter. It was a fun ride and without going into what’s happening there now, this is a good opportunity to look at my 12 years on the platform. Early in November, I downloaded my data and locked my Twitter account. This gave me all the data I needed. Using R, a few nifty libraries and the tweets.js file that was part of the download, I could gain quite a lot of insight.

There’s plenty of guides to getting going on Mastodon, aimed at people leaving Twitter. I just wanted to post a couple of technical points about making the switch that might be of interest to people who maintain webpages with Twitter content (feeds, embeds). Mastodon status updates (feed/timeline) Twitter provided a widget that meant that an account’s timeline could be embedded on a website.

There are lots of ways for runners and cyclists to analyse training data. A key question most fitness enthusiasts want to know is “how am I doing?”. “How you are doing” is referred to as form . Unsurprisingly, form can be estimated in many ways. One method is using training stress scores (acute training load and chronic training load) to assess form as training stress balance.