libnoise

Crates.iolibnoise
lib.rslibnoise
version1.1.2
sourcesrc
created_at2023-08-09 19:05:51.052226
updated_at2024-02-28 12:23:11.165863
descriptionA simple, performant, and customizable procedural noise generation library.
homepagehttps://github.com/cookiephone/libnoise-rs
repositoryhttps://github.com/cookiephone/libnoise-rs
max_upload_size
id940262
size6,973,823
SpoogieOogie (cookiephone)

documentation

https://docs.rs/libnoise

README

libnoise

format lint test codecov docs.rs Crates.io

A simple, performant, and customizable procedural noise generation library inspired by libnoise for C++ featuring:

  • Easy coherent noise generation through sources provided via Source
  • Modular generator creation by chaining adapters to modify and combine generator inputs and outputs, and the ability to flexibly create custom generators and adapters, all through the Generator trait
  • Efficient and cache friendly sampling of generators through NoiseBuffer and much of the generator complexity resolving at compile time
  • Easy visualization of generator outputs for debugging through Visualizer

Libnoise provides utilities to generate coherent noise and customize them by applying a variety of operations which modify and combine generators. With a focus on customizability, the library allows users to create custom generators and modifiers.

Most immediately relevant documentation can be found in Source and Generator docs.

Usage

First, add the dependency to your project by editing your Cargo.toml:

[dependencies]
libnoise = "1.1"

To get started easily, create a source generator using one of the many sources found in Source, and apply adapters documented in Generator. For a more detailed introduction, see the quickstart guide.

use libnoise::prelude::*;

// build a simplex noise generator seeded with 42
let generator = Source::simplex(42);

// sample the generator for input point [0.2, 0.5]
let value = generator.sample([0.2, 0.5]);

Note how the dimensionality, which is internally represented as a constant generic argument, is automatically inferred by sampling the generator with a 2-dimensional input point.

Naturally, we can create more interesting complex generators:

use libnoise::prelude::*;

// build a generator
let generator = Source::simplex(42)                 // start with simplex noise
    .fbm(5, 0.013, 2.0, 0.5)                        // apply fractal brownian motion
    .blend(                                         // apply blending...
        Source::worley(43).scale([0.05, 0.05]),     // ...with scaled worley noise
        Source::worley(44).scale([0.02, 0.02]))     // ...controlled by other worley noise
    .lambda(|f| (f * 2.0).sin() * 0.3 + f * 0.7);   // apply a closure to the noise

// sample the generator for input point [0.2, 0.5]
let value = generator.sample([0.2, 0.5]);

We can also use NoiseBuffer for efficiently filling n-dimensional arrays with noise, and Visualizer to get a visual representation of a given generator. The above generator produces the following image, when sampled for every pixel position:

image

It is common to interpret the 3rd or 4th dimension as time, allowing us to produce space-time noise such as:

image

Contributing

Contributors and feature suggestions are welcome!

Should you want to contact me directly, it is best via discord (username: oogie).

License

Libnoise is distributed under the terms of the MIT license.

See LICENSE-MIT for details.

Commit count: 126

cargo fmt