Hopefully I will soon break out of this funk of posting about either Mastodon or Twitter. But not yet! This post is to say that: I made a static archive of tweets for @quantixed and for @clathrin. There, you can read all my posts, which ended in 2022. How did I do it and why? I made the archive with this excellent tool written by Darius Kazemi.
Earlier this year I set up a bot on Mastodon. The bot, AlbumsX3, posts an album suggestion twice-a-day. Performance has been good. It has only missed a few posts due – I think – to server glitches. However, I have made a couple of tweaks to upgrade the bot since my last post, so I thought I would detail them here.
I migrated my personal Mastodon account from mastodon.social to biologists.social recently. If you’d like to do the same, I found this guide very useful. Note that, once you move, all your previous posts are left behind on the old instance. Before I migrated, I downloaded all of my data from the old instance. I thought I’d take a look at what I had posted to see if anything was worth reposting on biologists.social.
This is a brief review of macOS Mastodon clients that I’ve tried. It is unashamedly incomplete/non-exhaustive, but since the ones I found online from computing magazines literally look at one app, I am ahead of the pack here! tl;dr I prefer Ivory on macOS and prior to that, Mastonaut was OK. For clarity: I have not been asked or received payment to promote any software.
We have an analysis routine for proteomics data written for IgorPro. One output is a volcano plot. These plots show the fold change in one sample compared to another and plot that against a p-value to estimate how reproducible any changes observed are. This post is not about that software, but on the topic of how we can recreate this plot in R. What steps need to be considered?
I’ve posted in the past about analysing race results in R (most recently here). I ran the 2023 MK Marathon and wanted to have a look at the finishing times. The days of race results being made available as a csv or xls for easy analysis seem to be behind us. Instead they tend to be served up on multiple webpages of 50 athletes’ results at a time. Oh no, 29 pages of results and now Download option…. let’s scrape the data!
I’m not a big movie person. Nonetheless I have a media library with quite a few films in and I wondered how many “films to see before you die”-type movies I had in the collection, and how many were missing. I used R to find the answers. I’ve described previously how to get a plain text dump of a Plex database using WebTools-NG. I did that for the Movies library of my Plex Media Server.
I like to set up a standardised directory structure for RStudio projects. The idea came from here. In brief, the structure is: Data/ Output/Data/ Output/Plots/ Script/ My typical workflow is therefore to: select File > New Project in RStudio make a new directory and RProj file then use this R script or these shell commands to setup the directories. So far, so good. However, this process is a bit tedious.
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.
