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Noise-Extras
Noise & procedural generation code pieces that I didn't feel needed whole repos all to themselves.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
So I wrote an article on it here. You can find the code here.
One minor gripe, same as I've expressed on other posts: I think it is best to take care when choosing and discussing noise algorithms in articles. Specifically, where you discuss Perlin noise as an example for performance testing, this may unintentionally reinforce the problematic status-quo where it is considered the default for its purpose. Many sources gravitate towards Perlin as a first or primary solution for noise, but its square bias tendencies present an entirely unnecessary compromise for most applications. Readily-available Simplex-type noise replacements and drop-in 3D+ domain rotation mitigation measures can easily address its shortcomings, but people continue to use the uncorrected noise. A lot of this, I believe, stems directly from the overwhelming number of sources that teach the old noise in a vacuum, rather than in context. If we focus on teaching the right thing in newer sources, though, then slowly this can get better. I get that it's not the main focus of your article, it's just an effect that it can have.
Awesome to hear! If you want lib suggestions, I'm partial to FastNoiseLite (partially because I contributed to it, partially because it supports both simplex-type noise with good gradient vector tables, and domain rotation via setRotationType3D(...) and GetNoise(x, y, z)). There are definitely other options though.