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thomascountz 10 hours ago [-]
If you're into exploring this sort of thing yourself, I can extremely highly recommend Daniel Shiffman's Nature of Code[1]. It's among my top-5 recommended books about computing in general, let alone for algorithmic art.
Author here. I wrote this many years ago (2017?) while exploring techniques to create art that I could put up on my walls :-) If you enjoyed this article there are more similar ones linked on the main page: https://sighack.com/
liendolucas 10 hours ago [-]
Iteration 19 is particularly beautiful if you look at it with polarized glasses, it almost looks like a 3d effect.
smcameron 4 hours ago [-]
Curl Noise[1] is also cool. I've used it to create some gas giant planets for video games [2] though I used opensimplex noise [3] rather than perlin as the base noise, but either will work.
If you dig Perlin noise fields, the next stop is fBM (Fractional Brownian Motion). Inigo Quilez has a good article about it - https://iquilezles.org/articles/fbm/
beepbooptheory 1 hours ago [-]
Every article on that site is wonderful.
FeteCommuniste 8 hours ago [-]
Nice examples, I think I landed on that page quite a while ago. I love Processing and Perlin noise. One thing I enjoyed was using Perlin noise values to compute a "region" on the canvas and making the behavior of a particle depend on which region it was in. Examples:
Generative artist here: the beautiful thing about this exploration is that these techniques can be applied to ANY vector field, whether they originate in random noise or global simulations.
The reason these add so much visual interest to a simple noise function is that each pixels color now relies on many more of the random values. Generative art blossoms with this extra computational effort.
It turns out that adding noise to gradients is a really useful thing to do - so many new effects can be created with just a few additional parameters. Sadly, CSS and Canvas API gradients (linear, radial, conic) are very basic implementations (and SVG is not much more advanced).
Recently I did some work to add software gradient enhancements to my canvas library. Because these run on the CPU rather than GPU they're computationally intense, but still worth the effort just to see what can be done with different spreads (pad, repeat, reflect, transparent) and noise engine operations inserted while calculating stuff like gradient color selection, and pixel positioning.
Please make an HN post out of your generative bad hand writing. Very cool.
fractal618 3 hours ago [-]
I learned a lot about perlin noise when generating virtual worlds for Wurm Unlimited fascinating stuff and very satisfying when you get results you’re looking for.
tehrash 12 hours ago [-]
Great write up! I also dove in to this topic a while ago over at https://damoonrashidi.me/articles/flow-field-methods, but putting the live processing sketches in was a very nice touch! Good job, and nice outputs!
11 hours ago [-]
jadar 9 hours ago [-]
If you have played Minecraft, you have a pretty good idea what kind of things Perlin Noise can generate. Maybe not the structures but definitely the terrain is generated by Perlin noise. (At least it was in the 1.4.7 days when I was in the code.)
srean 12 hours ago [-]
Very beautiful.
I am a complete newbie, so I might be asking about something obvious -- does anyone know how some of these would relate to plotting random Polya vector fields ?
For example, one can take a sum of complex rational functions of the form
f_i(z) = r_i / (z - p_i)
where (r_i,p_i) are complex numbers drawn from some random point process, say a generalized Poisson one.
One needs to plot the conjugate of sum_i f_i(z).
EDIT: so many lovely pages pointed to in the comments !
Let me convey collective thanks to all, rather than clutter this page with individual thanks.
some beautiful effects and good ideas. My favs are iterations 8, 20, 25
deadbabe 6 hours ago [-]
One of the cool things to do with Perlin noise is to build a kinda predictable random number generator. Good for games.
neuropacabra 10 hours ago [-]
This is super nice article. Will revisit this one more time and try that out as well. In the age of AI slop, it is such a pleasure to read actual people blogs about what they do and are passionate about. Thank you this one!
[1]: https://natureofcode.com/
[1] https://www.cs.ubc.ca/~rbridson/docs/bridson-siggraph2007-cu... [2] https://github.com/smcameron/gaseous-giganticus [3] https://en.wikipedia.org/wiki/OpenSimplex_noise
https://020406.org/processing/PerlinNoiseBounds1.png
https://020406.org/processing/PerlinNoiseBounds2.png
https://020406.org/processing/PerlinNoiseBounds3.png
The Processing code I wrote to make them is here: https://github.com/Brian-Fearn/Processing/blob/main/PerlinNo...
The reason these add so much visual interest to a simple noise function is that each pixels color now relies on many more of the random values. Generative art blossoms with this extra computational effort.
Recently I did some work to add software gradient enhancements to my canvas library. Because these run on the CPU rather than GPU they're computationally intense, but still worth the effort just to see what can be done with different spreads (pad, repeat, reflect, transparent) and noise engine operations inserted while calculating stuff like gradient color selection, and pixel positioning.
Linear gradient demo test - https://scrawl-v8.rikweb.org.uk/demo/canvas-003.html
We used Perlin noise for demos of our Golang/BubbleTea terminal Glyph heatmap widget and then later with our Picture widget.
Live WASM demos of the Golang terminal programs:
https://nimblemarkets.github.io/ntcharts/demos/heatmap-perli...
https://nimblemarkets.github.io/ntcharts/demos/heatpicture-p... Press 't' to switch between glyph/image modes
I am a complete newbie, so I might be asking about something obvious -- does anyone know how some of these would relate to plotting random Polya vector fields ?
For example, one can take a sum of complex rational functions of the form
where (r_i,p_i) are complex numbers drawn from some random point process, say a generalized Poisson one.One needs to plot the conjugate of sum_i f_i(z).
EDIT: so many lovely pages pointed to in the comments ! Let me convey collective thanks to all, rather than clutter this page with individual thanks.
@ttctciyf you are marked dead. Not sure why.