I might need to manipulate and synthesize midi in R, so I spent the afternoon trying to make various packages work. They are all wrappers for python stuff. It wasn't a cake walk, but I finally made an mp3 of the top gun theme song = declaring victory
I was discussing with a colleague the other day that perhaps the best and indisputable random generator seed is the author' s own name.
The issue is R's set.seed() only accepts integer as random seed value. So I played around a little and finally managed to come up with a simple one-liner solution all using base R to use my own name as random seed.
I wrote a short blog post about it to explain my journey:
#rstats folks who switched from notebook/rmd/qmd oriented workflows to {targets}, how did you transition? Do you just precompute files with {targets} and then use these in your notebooks? Is rendering a notebook in itself a target? How do you do EDA now versus then?
I find it hard to adapt my analysis mindset to the targets framework
Even though I think #RStats is the superior choice when it comes to data anything, I think I might work on a python edition of my book on reproducibility. Those notebooks hosted on Github without any requirements.txt or Dockerfiles need to stop!
Also, if I do this, I'll be using tidyverse-inspired packages exclusively: siuba, plotnine and Quarto. But there's nothing like {targets} in #Python, and pkg dev isn't as polished either!
It's the beginnings of an #rstats package for experimental mangling of #MIDI files. TBH, it's my personal experimental hacky-code base wrapped in R package clothing. I'm messing with it constantly, and sharing in case others are interested. #genRativemusic#Rmuzak#rstatsmusic
Favourite resources for learning vim keybindings in RStudio and/or VSCode?
I’ve been programming for a few years now, but I still type like a distracted chimpanzee.
I know it’s worth learning to touch type. I feel like that’s a guaranteed win.
Vim is another story. I really don’t get it, at all. I’m a total noob. That said, I like learning from all types of resources, so long as the language used is clear for a beginner.
If I'm looking to use Docker to assist with making my research reproducible then should I rely on both Dockerfiles and Dockerimages or one or the other? As I understand it, the Dockerfile specifies how the Docker image will be built but an image can contain the scripts, original data, and correctly versioned software / libraries etc. So why not just / always publish the image?
I'm trying to integrate some public air quality data into my study. During a sanity check of the data I realized 3 of the measurement columns contain negative values! Does anyone have any idea if having negative value in such measurements is valid and how they should be interpreted?
Contacting the data manager is not as easy and might take me a week or two of emailing to get some answer. I wonder if #AirQuality folks here on fediverse have a quick answer.
Currently learning #Python as a long-time #RStats guy. Posting my thoughts as I go along.
R's {devtools} makes package development really nice:
Write code
Reload package with ctrl + shift + L
Test the new code
Go to (1).
I'm using #vscode for package development in Python, and I haven't found a workflow that feels half as nice as this. Am I missing something? Has anyone out found a system that does feel good to use?
I have a paper on crow behaviour under review that uses agent-based modelling in R to predict survival outcomes. One review is complete, but the editor emailed to ask for more reviewer recommendations because she is struggling to find willing reviewers.
Anyone fancing reviewing a lovely modelling paper about crows?
(1/2) Deploy a Shinylive App ✨ to Github Pages tutorial 👇🏼
I created this tutorial a day after the announcement of the shinylive R version at the Posit conference, using a dev version of the shinylive and httpuv packages. It was on my TODO list for quite a while to update the tutorial with the stable version of the core packages. Thanks to a PR from Ronak Shah 🙏🏼, I updated the tutorial and the supporting Docker 🐳.
I'm excited for the new #rstats ggplot2 version coming up that I helped out with. So I thought a fun game might be to post a plot every day and people can guess what the new thing is. No cheating by looking at the NEWS.md file!