{"categories":[{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/3"}],"enrichment":{"capability":"Generates OpenSimplex noise across 2D, 3D, and 4D coordinate spaces, with both scalar and NumPy array interfaces for performance-critical workloads.","skillfed_tags":["procedural-generation","noise-synthesis","graphics"],"use_cases":["Generate terrain heightmaps or procedural landscape data for games and simulations using 2D or 3D noise.","Create texture patterns, cloud formations, or natural-looking visual effects in graphics applications.","Seed random variation in machine learning or data augmentation pipelines where smooth, coherent randomness is needed.","Batch-process large coordinate arrays with noise2array/noise3array/noise4array for performance-critical scientific workloads.","Replace Perlin or Simplex noise in existing projects without patent concerns or directional visual artifacts."],"what_it_does":"OpenSimplex is a Python port of Kurt Spencer's OpenSimplex noise algorithm, a gradient noise function designed to overcome patent issues with Simplex noise while avoiding Perlin noise's directional artifacts. It generates smooth, coherent noise values across 2D, 3D, and 4D spaces, returning floats between -1.0 and 1.0. The package provides both scalar functions (noise2, noise3, noise4) for single-point queries and array-oriented variants (noise2array, noise3array, noise4array) that accept NumPy arrays for batch processing.\n\nThe library depends on NumPy for array optimizations aimed at heavier workloads and supports optional Numba integration for further speed gains through caching. It is seeded via a 64-bit integer or system time, allowing reproducible or varied noise generation. The API underwent breaking changes in v0.4.*, so existing code may require updates. Maintenance is dormant but stable; the maintainer prioritizes library stability over new core features.","worth_installing":"Yes, if you need patent-free gradient noise for procedural generation or scientific computing. The package is stable, has no known vulnerabilities, and installs cleanly with minimal friction. However, maintenance is dormant (last release 835 days ago), so expect no active development or rapid bug fixes\u2014verify that the current API and behavior suit your use case before committing to it."},"id":"opensimplex","links":{"html":"https://skillfed.io/packages/opensimplex","md":"https://skillfed.io/packages/opensimplex.md","pypi":"https://pypi.org/project/opensimplex/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2024-05-01","license_spdx":null,"license_treatment":"permissive","name":"opensimplex","python_support":"supports_current","summary":"OpenSimplex is a noise generation function like Perlin or Simplex noise, but better."},"popularity":{"monthly_downloads":81771,"position":14202,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.4.5.1"}