jwagner/simplex-noise.js
Simplex Noise.js
Simplex-noise.js is a mathematical noise generator and graphics library implemented in TypeScript. It computes smooth pseudo-random values across two, three, and four dimensions, producing organic patterns and spatial effects without relying on static image assets.
The library operates through a stateless mathematical engine that uses precomputed coordinate lookup tables and typed array buffers to manage numeric data. It supports deterministic seed injection, accepting custom pseudo-random number generator functions to initialize permutation tables with reproducible values for repeatable outputs.
Features
- Noise-Based Terrain Generation - Creates smooth, multi-dimensional pseudo-random mathematical values to build procedural textures, animations, and environments.
- Typed Arrays - Allocates underlying numeric buffers explicitly using typed arrays to maximize memory locality during computation.
- CPU Simplex Noise Generators - Produces smooth pseudo-random values across two, three, and four dimensions for procedural content.
- Procedural Noise Textures - Acts as a lightweight graphics library for computing smooth pseudo-random patterns across two, three, and four dimensions.
- JavaScript Simplex Noise Implementations - Provides a fast mathematical noise generator producing multi-dimensional pseudo-random values for procedural graphics and animations.
- Typed Array Allocators - Precomputes coordinate lookup tables in flat typed arrays to eliminate runtime allocation overhead during mathematical sampling.
- Reproducible Randomizers - Provides a seeded mathematical generator that produces reproducible pseudo-random sequences using custom random functions.
- Simplex Coordinate Projections - Transforms multi-dimensional coordinates into skewed simplex grid coordinates using mathematically derived scaling factors.
- Random Number Generator Seeding - Accepts custom random number generator functions to initialize permutation tables with reproducible values.
- Procedural Texture Generators - Creates smooth, multi-dimensional patterns and textures for graphics without relying on static image assets.
- Multi-Dimensional Integration - Generates smooth pseudo-random values across two, three, or four dimensions for simulations and spatial effects.
- Stateless Pure Libraries - Encapsulates noise generation logic inside pure functions relying entirely on local stack variables and precomputed constants.
