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[](https://swiftpackageindex.com/kelvin13/swift-noise)
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[](https://swiftpackageindex.com/kelvin13/swift-noise)
[](https://swiftpackageindex.com/tayloraswift/swift-noise)
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[](https://swiftpackageindex.com/tayloraswift/swift-noise)
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</div>
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**`swift-noise`** is a free, pure Swift procedural noise generation library. The library product has no dependencies and does not import Foundation or any system frameworks.
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**`swift-noise`** is a free, pure Swift procedural noise generation library. The library product has no dependencies and does not import Foundation or any system frameworks.
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All popular types of procedural noise are supported, including three [gradient noises](https://en.wikipedia.org/wiki/Perlin_noise) (often called Perlin or simplex noises), and two [cellular noises](https://en.wikipedia.org/wiki/Worley_noise) (sometimes called Worley or Voronoi noises).
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All popular types of procedural noise are supported, including three [gradient noises](https://en.wikipedia.org/wiki/Perlin_noise) (often called Perlin or simplex noises), and two [cellular noises](https://en.wikipedia.org/wiki/Worley_noise) (sometimes called Worley or Voronoi noises).
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`swift-noise` includes a [fractal brownian motion](https://thebookofshaders.com/13/) (FBM) noise composition framework, and a [disk point sampler](https://en.wikipedia.org/wiki/Supersampling#Poisson_disc) (often called a Poisson sampler), for generating visually even point distributions in the plane. `swift-noise` also includes pseudo-random number generation and hashing tools.
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`swift-noise`’s entire public API is [documented](doc/1.0.0).
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`swift-noise`’s entire public API is [documented](https://swiftinit.org/hist/swift-noise:master/noise).
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## Building
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Build *Noise* with the Swift Package Manager. *Noise* itself has no dependencies, but the tests use [`swift-png`](https://github.com/kelvin13/swift-png) to view the generated noise.
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Build *Noise* with the Swift Package Manager. *Noise* itself has no dependencies, but the tests use [`swift-png`](https://github.com/tayloraswift/swift-png) to view the generated noise.
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