OpenSimplex2 VS NoiseNormalizer

Wow you have been playing with noise for a while :) . It amazes me all the different noises that exist now.. Perlin, Simplex, OpenSimplex, OpenSimplex2S, OpenSimplex2F, Worley... If you are curious about OpenSimplex https://github.com/KdotJPG/OpenSimplex2

Probably true, although a neat repo for open simplex is https://github.com/KdotJPG/OpenSimplex2

This may not answer what you're actually looking for - but a few years ago I found a library for coherent noise in Java, which at least meets my needs. I use bits and pieces of the Open Simplex Noise implementation from that library. It's unlicense/CC0, so easily copy-paste-able straight in to one's own project. https://github.com/KdotJPG/OpenSimplex2/

So I was looking for a noise function, and I found this repo from the author of the OpenSimplex algorithm. And in the GLSL implementation, which is the one I'm gonna use, since I want to generate terrain with compute shaders, the function%20%7B) looks like this:

If you want to feel safer from that, you might opt to use one of these instead. Use the ImproveXY endpoint to get a Z that repeats after 500.5626833874055. Go up one directory and into the glsl directory if you need GLSL versions instead .

Fair. I definitely agree Simplex has some characteristics that don't work great in some places. Especially when you threshold near zero of a single octave. Have you tried OpenSimplex2S? It's made to be less "bubbly" than standard simplex. In own repo, In FastNoiseLite, [Shader preview (3D noise)[https://www.shadertoy.com/view/ttdGR8]. Both the 2D function and 2D slices of the 3D function might be worth looking into if you haven't yet.

Here's a link to the original implementation: github.com/KdotJPG/OpenSimplex2/blob/master/glsl/OpenSimplex2.glsl

Github Repo: https://github.com/KdotJPG/NoiseNormalizer/

I think Simplex 4D could benefit from that in almost as good of a way. I haven't tested this myself, but the unskew constant to change to would be 0.3618033988749895 or changing the - to a + in the unskew constant so it becomes (5.0f + SQRT5) / 20.0f. I computed this by taking the unskew constant, writing out the full unskew matrix, multiplying by a rotation matrix, seeing that it can be converted back into a constant, then seeing that it just amounts to the sqrt term sign change. The new scale value will be (TBD - running NoiseNormalizer as I type this, will update with result).