Noise Planets | Hacker News Reader

Noise Planets

avinayak.github.io

161 pointsatulvi16 comments

> I found this neat technique, to find random points in a circle where a random radius r and angle theta are chosen and the x,y points are obtained as x = centerX + r * cos(theta) and y = centerY + r * sin(theta)

This misses the crucial point of the technique described in the linked Stackoverflow answer: that r cannot be a uniformly distributed random value if you want a uniform distribution of points in a circle. Rather you need

    r = R * sqrt(random())

where R is the radius of the circle and random() gives a uniform distribution of random numbers between 0 and 1.

Or just do the classic rejection sampling technique:

  do {
      x = random(-R, R)
      y = random(-R, R)
  } while (x*x + y*y > R*R)

Well, that’s what the author says they started with, before replacing it with the non-uniform algorithm.

That seems awfully inefficient.

Not really, about π/4 = 79% of the times you will have a single iteration. The expected number of iterations is the geometric series with this ratio, which is smaller than 2.

In practice it’s likely faster than the method that uses polar coordinates due to the latter’s reliance on transcendental functions.

The article uses original work of Tyler Hobbs [1] who apparently creates fascinating abstract art via programming.

[1] https://twitter.com/tylerxhobbs

What keeps the lines from intersecting? Is that a property of "Perlin noise"?

I think it comes from the noise field being relatively smooth, and the particles taking such small steps each frame.

The flowlines of any vector field cannot intersect, because that would mean the flowline has two tangent vectors at that point. For smooth vector fields, they cannot merge either, an intuition for that is perhaps that you could theoretically run the flow "in reverse", which would turn a merger into a split, and that's not possible.

'Procedural Landscapes with Overhangs' by Gamito and Musgrave covers exactly this!

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.2.1...

The Perlin noise is generating a scalar field in this case (which gives the direction of the movement vector at each point). Here's a very similar bit of code that can be tweaked easily: https://openprocessing.org/sketch/494102/

Setting the particle speed to more than about 0.5 (on line 46) results in "aberrations". The dynamics are quite interesting and I'm not sure exactly what's going on, but I think wetmore's answer is correct—when the steps are small enough, everything remains as smooth as the underlying scalar field produced by Perlin noise.

In his code after "and now we apply flow fields and try to move these points", the code is errant. It will produce errors if you try to run it.

The variable "m" in draw() should be changed to "points".

The variable "h" in draw() should be changed to "t".

a while back I got into fractal noise, simd instructions, and unity and made a bunch of planets: https://www.youtube.com/watch?v=dqNXpU9d2_I

More like noise circles rather than spheres. Still looks good though.

Reminded me of the recent Sci-fi DUST episode, Avarya https://www.youtube.com/watch?v=YvLH0sy_lu8

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