Exercises in Random Shaping

The exercises I have been playing with are mostly to do with random walk, and filtering the randomness or controlling the density.

This program picks one of 8 possible directions to walk in, each frame, but the distribution is made 'more gaussian' (not sure of terminology) so that the density is clustered around one particular direction. This averages out the path to be in one direction overall, even though it makes many deviations.

This is another random walk, moving in one of 4 directions and then drawing a square. The walk is influenced though, so I think this defines it as a filtered randomness. A central point is defined, and the distance to that point is checked at each step. Through mathematical wizardry, I convert this information into an influence value, so the decision it makes to walk in one direction or another is slightly influenced by its proximity to this point. This effectively reins it in, and can create pretty cool landscapes (more on this later, it is the basis for my Project 2).

This one uses the technique of averaging the neighbouring points in a point array to draw successively less distorted circles. I managed to find out how to control how much it averages the points when passing through the filter (rather than just making the current point equal to the average of it's neighbours).

This is just visualising density, in the y axis. This uses the method of summing random numbers. I hooked up some controls so its possible to play around with which axes are being density controlled, how aggressively gaussian the distribution is, and how big the particles are.