Possibly interesting post from Casey Muratori, regarding random placement of grass in games: https://caseymuratori.com/blog_0013, using blue noise.
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Terr_
> Consider when the algorithm places a point p and then samples its annulus to get a new point q.
I was confused for a while thinking p and q were swapped here, relative to the visualization below. [0] However I now think what I missed is that that the visualization is showing two points that are already firmly-established, and the question is where a potential third (unseen, unnamed) point could be placed.
So metaphorically speaking, it's about picking a new direction of travel that isn't guaranteed to be into your own recent footsteps.
[0] You might say I have problems minding my p's and q's.
PiXeL161616
Never found a way to do this per-pixel in a shader, Bridson's needs the active list. Ended up hashing cells and jittering inside them instead.
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hingler36
I love these kinds of problems, because they try to produce what humans perceive as random instead of something truly random. Another great example of this is blue noise
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addag
I'm wondering if it can be used as a low-discrepancy sequence
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WithinReason
I see the generated points often form lines which would cause aliasing in computer graphics, why not use low discrepancy sequences instead?
yanjunnf
Magical algorithm
jonstewart
Oh, that’s rather a different sort of disk sampling than I imagined.
Still one of the most satisfying debug UIs I ever came up with.
https://akkartik.name/post/2023-11-04-devlog
Folks may find https://observablehq.com/@fil/poisson-distribution-generator... useful
Off-topic but I quite like another post about relationships on this site: https://stripeacross.com/posts/no-bf-22/
Possibly interesting post from Casey Muratori, regarding random placement of grass in games: https://caseymuratori.com/blog_0013, using blue noise.
> Consider when the algorithm places a point p and then samples its annulus to get a new point q.
I was confused for a while thinking p and q were swapped here, relative to the visualization below. [0] However I now think what I missed is that that the visualization is showing two points that are already firmly-established, and the question is where a potential third (unseen, unnamed) point could be placed.
So metaphorically speaking, it's about picking a new direction of travel that isn't guaranteed to be into your own recent footsteps.
[0] You might say I have problems minding my p's and q's.
Never found a way to do this per-pixel in a shader, Bridson's needs the active list. Ended up hashing cells and jittering inside them instead.
I love these kinds of problems, because they try to produce what humans perceive as random instead of something truly random. Another great example of this is blue noise
I'm wondering if it can be used as a low-discrepancy sequence
I see the generated points often form lines which would cause aliasing in computer graphics, why not use low discrepancy sequences instead?
Magical algorithm
Oh, that’s rather a different sort of disk sampling than I imagined.