Here are some of my generative pieces that I made a while ago. I spent a lot of time writing the code that would produce these images, they're very intentional, and they're nothing like what any "AI" image generator would spit out.
Life has been 'lifeing'. Everything is chaotic and I'm just patiently waiting for May for a vacation. In the meantime, I am slowly working on my artpack package. I'm creating convenience functions, group_sample() and group_slice() that will allow you to quickly sample/slice entire groups out of data frames. This is something I personally do a lot for my art. Being able to drop groups of data can lead to some cool visuals sometimes: #rtistry w/ #ggplot2 in #rstats.
New blog post about data art!
Have you ever wondered:
What is data-driven art?
Why do people make data art?
How do I get started making my own?
Then this blog post is for you!
I've started collecting together some of my examples of data-driven art (with accompanying code) into a gallery
Link: https://nrennie.rbind.io/data-art/
(Blog post coming soon about what I think data art is and why it's useful, alongside a tutorial-style example!)
A little bit of #DataArt on a Monday afternoon! Can you guess the data?
Playing with flow fields and pixel sorting, selectively removing colour by switching to grey only for certain hues. Made using R
Trying more flow fields through the same process of pixel sorting then selectively overlaying the original. This one is nice
Choosing pixels from a sorted or unsorted copy of a flowfield image depending on the hue of the original image. Anything from blue-green to purple-red gets copied, otherwise we see a sorted version.
I recently had fun making a new cover image for Mastodon by making treemaps of colours used in Bob Ross paintings (columns are seasons and rows are episodes)!
Painting data from #TidyTuesday
Colours extracted using {eyedroppeR}
Pixel analysis in #RStats
Plotting with {treemapify}