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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 main features of jwagner/simplex-noise.js are: Noise-Based Terrain Generation, Typed Arrays, CPU Simplex Noise Generators, Procedural Noise Textures, JavaScript Simplex Noise Implementations, Typed Array Allocators, Reproducible Randomizers, Simplex Coordinate Projections.
Projects with overlapping indexed features include: accord-net/framework — This project is a scientific computing framework for the .NET ecosystem, providing a comprehensive suite of libraries… anthonynsimon/bild — Bild is an image processing library implemented in the Go programming language. It provides a collection of… chancejs/chancejs — Chance is a JavaScript library for generating random data, designed to produce realistic test data for automated tests… azgaar/fantasy-map-generator — This project is a web-based procedural fantasy map generator and interactive map editor. It serves as a worldbuilding… fogleman/craft — Craft is a multiplayer voxel sandbox written in C. It utilizes an OpenGL voxel engine to render a block-based world… jdah/minecraft-weekend — minecraft-weekend is a voxel engine designed for rendering infinite three-dimensional environments. It utilizes…
This project is a scientific computing framework for the .NET ecosystem, providing a comprehensive suite of libraries for numerical analysis, statistics, and mathematical optimization. It serves as a foundational toolkit for developing applications in machine learning, digital signal processing, and computer vision. The framework provides specialized toolkits for training and deploying predictive models, including neural networks, support vector machines, and decision trees. It further distinguishes itself with deep integrations for real-time visual analysis, such as object tracking and facia
Bild is an image processing library implemented in the Go programming language. It provides a collection of algorithmic engines for image manipulation, including a convolution kernel engine for filtering, an image blending tool for layer composition, and a procedural noise generator for creating synthetic textures. The project is distinguished by its procedural generation capabilities, implementing Perlin, Gaussian, binary, and uniform noise algorithms to produce random pixel distributions and organic patterns. It also features a command-line interface that allows users to apply visual effect
Chance is a JavaScript library for generating random data, designed to produce realistic test data for automated tests and prototypes. It uses a Mersenne Twister pseudo-random number generator that accepts an optional seed value, enabling reproducible sequences of random values across multiple runs. The library provides a wide range of generators for common data types, including random integers, floats, booleans, characters, strings, and dates, all with configurable ranges and character pools. It can generate realistic geographic data like addresses, as well as financial data such as credit c
This project is a web-based procedural fantasy map generator and interactive map editor. It serves as a worldbuilding cartography tool for creating detailed geographical landmasses, including heightmaps, biomes, and river systems. The tool includes a procedural name generator that produces fantasy names using configurable training sets and syllable rules. It further allows for the design of political borders, cultural identities, and the simulation of religious expansion across a fictional world. The capability surface covers digital cartography and fictional geography design, including the