simplex-noise 1.0.1

Python wrapper for Pure C Simplex Noise library

Simplex Noise Library

A high-performance, cross-platform C library for generating simplex noise - perfect for procedural generation, graphics programming, and game development.

What is Simplex Noise?

Simplex noise is an improved version of Perlin noise that's faster and produces better-looking results. It's widely used in:

• Game Development - Terrain generation, texture synthesis, procedural content
• Computer Graphics - Heightmaps, cloud generation, organic patterns
• Scientific Visualization - Data representation, simulation textures
• Art & Design - Procedural art, creative coding projects

Features

Core Capabilities

• Multi-dimensional noise - 1D, 2D, 3D, and 4D generation
• Multiple noise types - Classic, ridged, billowy, and fractal variants
• High performance - Over 28 million samples per second for 2D noise
• Image generation - Create PNG and PPM images from noise patterns
• Flexible configuration - Customizable parameters and multiple PRNG algorithms
• Cross-platform - Works on Windows, macOS, Linux, and more
• Python bindings - Easy-to-use Python wrapper with NumPy integration

Noise Variants

• Classic Simplex - Standard smooth noise patterns
• Ridged Noise - Sharp, mountain-like formations
• Billowy Noise - Soft, cloud-like textures
• Fractal Noise - Complex, layered patterns with multiple octaves
• Domain Warping - Twisted, distorted effects

Quick Start

Installation

C Library

git clone https://github.com/paredezadrian/simplex-noise.git
cd simplex-noise
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j$(nproc)
sudo make install

Python Bindings

pip install simplex-noise

Basic Usage

C Library

#include <simplex_noise.h>
#include <stdio.h>

int main() {
    // Initialize with a seed
    simplex_noise_init(12345);

    // Generate 2D noise
    double noise_value = simplex_noise_2d(1.0, 2.0);
    printf("Noise value: %.6f\n", noise_value);

    // Generate fractal noise (multiple octaves)
    double fractal = simplex_fractal_2d(1.0, 2.0, 4, 0.5, 2.0);
    printf("Fractal noise: %.6f\n", fractal);

    return 0;
}

Python Bindings

from simplex_noise import SimplexNoise
import numpy as np

# Initialize noise generator
noise = SimplexNoise(seed=42)

# Generate single values
value = noise.noise_2d(1.0, 2.0)
print(f"2D noise: {value}")

# Generate arrays
x = np.linspace(0, 10, 100)
y = np.linspace(0, 10, 100)
X, Y = np.meshgrid(x, y)
noise_array = noise.noise_2d(X, Y)

# Generate fractal noise
fractal = noise.fractal_2d(X, Y, octaves=4, persistence=0.5, lacunarity=2.0)

# Generate images
noise.generate_image("terrain.png", width=512, height=512,
                    color_mode="heightmap", octaves=6)

Advanced Configuration

#include <simplex_noise.h>

int main() {
    // Create custom configuration
    simplex_config_t config = simplex_get_default_config();
    config.seed = 42;
    config.octaves = 6;
    config.persistence = 0.7;
    config.lacunarity = 2.0;
    config.enable_caching = 1;

    // Initialize with custom settings
    simplex_noise_init_advanced(&config);

    // Generate noise with your settings
    double noise = simplex_noise_2d(1.0, 2.0);

    // Clean up when done
    simplex_cleanup();

    return 0;
}

Examples

The library includes several example programs to get you started:

# After building
cd build
./example_2d      # Visual 2D noise patterns
./example_3d      # 3D noise slice visualization
./example_config  # Configuration system demo
./example_fractal # Different fractal noise types
./example_image   # Generate noise images (PNG/PPM)

Image Generation

Create beautiful images from noise patterns:

Basic Usage

#include <simplex_image.h>

int main() {
    // Create image configuration
    simplex_image_config_t config = simplex_get_default_image_config();
    simplex_set_image_size(&config, 512, 512);
    simplex_set_image_filename(&config, "my_noise.ppm");
    simplex_set_color_mode(&config, SIMPLEX_COLOR_HEIGHTMAP);

    // Generate image
    simplex_generate_2d_image(&config);

    return 0;
}

Image Types

• Grayscale - Classic black and white noise
• RGB - Color noise patterns
• Heightmaps - Terrain-like visualizations
• Terrain - Natural landscape colors
• 3D Slices - Cross-sections of 3D noise

Supported Formats

• PPM - Portable pixmap (widely supported)
• PGM - Portable graymap (grayscale)
• PNG - Portable Network Graphics (with libpng)

Performance

The library is optimized for speed and efficiency:

• 2D Noise: 28.82 million samples/second
• 3D Noise: 15.2 million samples/second
• Fractal Noise: 2.1 million samples/second
• Array Generation: 45.6 million samples/second

Configuration Files

You can save and load configurations in multiple formats:

INI Format

[core]
seed=12345
octaves=6
persistence=0.7
lacunarity=2.0

[performance]
enable_caching=1
enable_profiling=1

JSON Format

{
  "simplex_noise_config": {
    "core": {
      "seed": 12345,
      "octaves": 6,
      "persistence": 0.7,
      "lacunarity": 2.0
    },
    "performance": {
      "enable_caching": true,
      "enable_profiling": true
    }
  }
}

API Reference

Core Functions

• simplex_noise_init(seed) - Initialize with seed
• simplex_noise_1d(x) - Generate 1D noise
• simplex_noise_2d(x, y) - Generate 2D noise
• simplex_noise_3d(x, y, z) - Generate 3D noise
• simplex_noise_4d(x, y, z, w) - Generate 4D noise

Fractal Functions

• simplex_fractal_2d(x, y, octaves, persistence, lacunarity) - 2D fractal noise
• simplex_fractal_3d(x, y, z, octaves, persistence, lacunarity) - 3D fractal noise

Noise Variants

• simplex_ridged_2d(x, y) - Ridged noise
• simplex_billowy_2d(x, y) - Billowy noise
• simplex_domain_warp_2d(x, y, strength) - Domain warping

Configuration

• simplex_load_config(filename, type, config) - Load configuration
• simplex_save_config(filename, type, config) - Save configuration
• simplex_print_config(config, format) - Print current settings

Building from Source

Prerequisites

• C99 compatible compiler (GCC, Clang, MSVC)
• CMake 3.12+

Build Options

cmake .. -DCMAKE_BUILD_TYPE=Release \
         -DSIMPLEX_ENABLE_SIMD=ON \
         -DSIMPLEX_BUILD_TESTS=ON \
         -DSIMPLEX_BUILD_EXAMPLES=ON

Testing

Run the test suite to verify everything works:

cd build && ctest

Use Cases

Game Development

// Generate terrain heightmap
for (int y = 0; y < height; y++) {
    for (int x = 0; x < width; x++) {
        double height = simplex_fractal_2d(x * 0.01, y * 0.01, 6, 0.5, 2.0);
        heightmap[y * width + x] = height;
    }
}

Texture Generation

// Generate procedural texture
for (int y = 0; y < texture_height; y++) {
    for (int x = 0; x < texture_width; x++) {
        double noise = simplex_noise_2d(x * 0.1, y * 0.1);
        texture[y * texture_width + x] = (noise + 1.0) * 0.5; // Normalize to 0-1
    }
}

Animation

// Animate noise over time
for (int frame = 0; frame < num_frames; frame++) {
    double time = frame * 0.1;
    double noise = simplex_noise_3d(x, y, time);
    // Use noise value for animation
}

Contributing

We welcome contributions! Here's how to get started:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Ensure all tests pass
6. Commit your changes (git commit -m 'Add amazing feature')
7. Push to your branch (git push origin feature/amazing-feature)
8. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Ken Perlin for the original Simplex Noise algorithm
• The open-source community for inspiration and feedback
• Contributors and users for their support

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: See the examples and API reference above

---

Ready to create amazing procedural content? Clone the repository and start generating noise today!