Animation of the algorithm

I am excited to tell you that I just released the alpha version of my “Pydont's” book, a book that compiles all my “Pydon't” articles. You can get the book at leanpub: leanpub.com/pydonts.

In this first post I want to share with you guys a piece of code I wrote to "solve" a problem where geometry meets optimization. I say "solve" because I didn't actually do anything that fantastic regarding the actual problem I address, but rather developed a small tool to help visualize the geometrical part of the problem. Even so, I do believe that for the smaller cases my tool can solve the problem.

The problem is along the lines of: define an energy function whose value depends on the positions of points in a sphere, and now try to minimize/maximize it (depending on a parameter). That is it. I used my coding skills to write an algorithm that solves this when the number of points is small, and that lets me see the creation of the solution: I create a random distribution of points and then let them adjust themselves to their desired positions, hopefully reaching the desired minimum/maximum.

In here you can find the report I wrote for this, in English. The code, some figures and some animations (GIFs like the one up there) can be found here.

If you liked this article and would like to support the mathspp project, then you may want to buy me a slice of pizza 🍕.

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