Cellaris

A modern and efficient cellular automaton simulation framework built for researchers and enthusiasts.

Overview

Cellaris is a powerful tool for simulating and visualizing cellular automata systems. It provides an intuitive interface for creating, running, and analyzing various cellular automaton models. Perfect for academic research, educational purposes, and computational experiments.

Features

• 🚀 High-performance simulation engine with WebGL acceleration
• 📊 Real-time visualization with customizable rendering options
• 🎨 Customizable cell states and rules with support for multi-state automata
• 💾 Save and load simulation states in multiple formats (JSON, CSV)
• 🔄 Multiple simulation patterns with preset configurations
• ⚙️ Configurable parameters with real-time updates
• 📈 Data export and analysis tools
• 🎯 Pattern detection and statistics
• 🔍 Zoom and pan controls
• ⌨️ Keyboard shortcuts for common actions

Technical Requirements

• Node.js >= 14.x
• Modern web browser with WebGL support
• 4GB RAM minimum
• Graphics card with OpenGL 3.0+ support

Installation

git clone https://github.com/andishe-wpd/Cellaris.git

README.md

cd Cellaris

npm install

Development Setup

npm run dev

Production Build

npm run build

npm start

Advanced Usage

Pattern Creation

const customPattern = new Cellaris.Pattern({
  name: 'Custom Glider',
  matrix: [
    [0, 1, 0],
    [0, 0, 1],
    [1, 1, 1]
  ],
  rules: {
    survive: [2, 3],
    birth: [3]
  }
});

patterns.js

Performance Optimization Tips

• Use appropriate cell sizes for your simulation scale
• Enable WebGL acceleration for large grids
• Implement boundary optimizations for infinite grids
• Use worker threads for complex rule calculations

Keyboard Shortcuts

• Space: Play/Pause
• R: Reset
• S: Save state
• L: Load state
• +/-: Zoom in/out
• Arrow keys: Pan view

API Documentation

Core Classes

• Cellaris.Simulation: Main simulation controller
• Cellaris.Grid: Grid management and cell state handling
• Cellaris.Renderer: Visualization engine
• Cellaris.Pattern: Pattern definition and manipulation
• Cellaris.Rules: Rule set implementation

Events

• onStep: Triggered after each simulation step
• onStateChange: Triggered when cell states change
• onPatternLoad: Triggered when loading patterns
• onReset: Triggered on simulation reset

Examples

Check the /examples directory for:

• Basic Game of Life implementation
• Custom rule sets
• Pattern generators
• Integration examples
• Performance benchmarks

Contributing Guidelines

1. Code Style
   • Use ESLint configuration
   • Follow TypeScript best practices
   • Document public APIs
2. Testing
   • Write unit tests for new features
   • Ensure all tests pass before submitting PR
   • Include performance benchmarks if relevant

License

MIT License - See LICENSE file for details

Community

• Discord: [Join our server]
• Twitter: @CellarisProject
• Monthly virtual meetups
• Academic collaboration opportunities

Made with ❤️ by the Cellaris Team

This enhanced version includes more technical details, examples, and structured information that will help users better understand and utilize the Cellaris framework.