10-06 Field/Distribution

Some Field-Producing Algorithms

Here are a few simulation algorithms that can fill a page in an interesting way. I chose these because I was able to find nice tutorials/demos; this is by no means a restricted list.

Many more algorithms are described in these resources:

Flow Fields

Here’s an excellent Observable notebook with interactive illustrations of Perlin Noise flow fields:

Here’s Dan Shiffman offering an explanation as well on the Coding Train.

Here’s a p5 demo  I made.

Examples of artworks using Perlin Noise flow fields.

By Nadieh Bremer:

By Tyler Hobbs:

By Mark Webster:

By Lionel Radisson:

By Fred Briolet:

By Itay Niv:

By Julien Gachadoat:

By Manolo Gamboa Naon:

By Alexis Colby:

By Jessica In:

Blending Algorithmic Approaches

In this article, Tyler Hobbs shows how different algorithms (including circle packing) can be used to seed the initial positions of moving particles — which can affect how a Perlin Noise flow field looks.

In this example (discussed here), Jason Webb shows how a Diffusion-Limited Aggregation simulation can be expressively altered, when the diffusing particles are not simply moving in a random way, but are moving along gradients of another simulation (in this case, a Perlin Noise flow field).

In this example below, a creator has accelerated a Physarium simulation by seeding the terrain with Perlin Noise, instead of having the terrain arise (slowly) exclusively through the actions of the particles: