Noise & Fields
Procedural noise generation for terrain, textures, and flow fields
This visualizer demonstrates Perlin noise and Simplex noise algorithms used for terrain generation, texture synthesis, and flow field creation in games. Adjust octaves, persistence, and scale to see how these parameters affect the generated patterns. Used in games for biome generation, heightmap creation, and organic-looking textures.
System Overview
Noise functions generate smooth, continuous values that appear random but are deterministic. Perlin noise and its variants (Simplex, OpenSimplex) are fundamental to procedural generation, creating natural-looking patterns from simple mathematical functions.
By combining multiple octaves (layers) of noise at different frequencies and amplitudes, we create complex, fractal-like patterns that mimic natural phenomena like terrain, clouds, and textures.
Why Games Use This
- Infinite Content: Generate vast worlds without storing every detail
- Deterministic: Same seed always produces the same result
- Performance: Compute on-demand, cache only what's needed
- Variation: Create unique experiences while maintaining consistency
- Natural Appearance: Smooth, organic patterns that feel hand-crafted
Key Parameters
- Scale: Controls the "zoom level" - smaller values create larger features
- Octaves: Number of noise layers - more octaves = more detail
- Persistence: How much each octave contributes - controls roughness
- Lacunarity: Frequency multiplier between octaves - controls detail spacing
- Seed: Determines the specific pattern generated
Failure Modes
- Too many octaves: Performance degrades, patterns become too busy
- Extreme persistence: High values create harsh, unnatural patterns
- Poor scale choice: Features too large or too small for intended use
- Non-deterministic: Using system random instead of seeded RNG breaks reproducibility
- Memory issues: Pre-generating large heightmaps can exhaust memory
Scaling Behavior
Noise generation is O(1) per sample, but octaves multiply the cost. For real-time applications, limit octaves to 4-6. For pre-computed content, 8+ octaves are feasible.
Memory scales with resolution: a 1024×1024 heightmap uses 1MB (8-bit) or 4MB (32-bit float). Consider chunking or streaming for large worlds.
Related Algorithms
- Simplex Noise: Improved version with better computational properties
- Worley/Voronoi Noise: Cell-based patterns for organic textures
- fBm (Fractal Brownian Motion): Standard multi-octave noise
- Ridged Noise: Absolute value creates sharp ridges
- Curl Noise: Divergence-free vector fields for flow
- Blue Noise: Poisson disk sampling for even distribution
Free Tools & Libraries
- FastNoise: C++ noise library with multiple algorithms
- noisejs: JavaScript Perlin/Simplex implementation
- p5.js: Built-in noise() function
- Three.js: Noise utilities for 3D generation
- ShaderToy: GPU-accelerated noise in GLSL
System-Thinking Prompts
- What happens if this scales 100×? How does performance degrade?
- Where does this break? What edge cases cause artifacts?
- How could players exploit deterministic generation? Can they predict patterns?
- Which parameter dominates behavior? Scale, octaves, or persistence?
- What happens at extreme values? Too many octaves, zero persistence, etc.
- How does seed choice affect gameplay? Can we guarantee interesting seeds?
- What's the minimum viable noise? Can we simplify further?