Just found this package from the new-packages-feed channel on Slack. Really nice one!
Several days back, I created a Julia wrapper of https://github.com/JuliaReinforcementLearning/FastNoise2.jl . I think both packages share a lot of utilities. But one thing which is missing in that wrapper is native GPU support. Looking into the source code of CoherentNoise.jl, I'm wondering how much extra work would it need to add GPU support for some common noise like OpenSimplex2?
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First of all, congratulations on this great package! ๐ I work a lot with generation of random images in geostatistics (GeoStats.jl) and it is nice to see more algorithms available.
May I suggest sampler_type(rng=...) instead of sampler_type(seed=...)? In Julia, whenever we want to guarantee reproducibility with random numbers we pass the generator object instead of the seed, and it goes as the first positional argument instead of a keyword argument. See the rand docstring for example.
Hey, first thanks for this package. The content is awesome and the docs are super nice!
I would like to use some of the examples you show in your table, but it's hard to know which exact combination was used (as code).
It would be great to have this in the table displayed here (https://mfiano.github.io/CoherentNoise.jl/dev/algorithms/).