Cohen’s d (wiki) is a statistic used to indicate the standardised difference between two means. Resarchers often use it to compare the averages between groups, for instance to determine that there are higher outcomes values in a experimental group than in a control group.
Researchers often use general guidelines to determine the size of an effect. Looking at Cohen’s d, psychologists often consider effects to be small when Cohen’s d is between 0.2 or 0.3, medium effects (whatever that may mean) are assumed for values around 0.5, and values of Cohen’s d larger than 0.8 would depict large effects (e.g., University of Bath).
I really like generative art, or so-called algorithmic art. Basically, it means you take a pattern or a complex system of rules, and apply it to create something new following those patterns/rules.
When I finished my PhD, I got a beautiful poster of where the k-nearest neighbors algorithms was used to generate a set of connected points.
My first piece of generative art.
As we recently moved into our new house, I decided I wanted to have a brother for the knn-poster. So I did some research in algorithms I wanted to use to generate a painting. I found some very cool ones, of which I unforunately can’t recollect the artists anymore:
However, I preferred to make one myself. So we again turned to the work of the author that made the knn-poster: Marcus Volz.
He has written (in R) many other algorithms. And we found that one specifically nicely matched the knn-poster. His metropolis – or generative city:
However, I wanted to make one myself, so I download Marcus code, and tweaked it a bit. Most importantly, I made it start in the center, made it fill up the whole space, and I made it run more efficient so I could generate a couple dozen large cities quickly, and pick the one I liked most. Here’s the end result: