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Python Implementation - Original Fractal Generator

This directory contains the original Python implementation of the fractal generator web application that was deployed on Heroku.

Contents

  • app.py - Main Flask web application
  • ChaosFinder.py - Automatic generation of discrete chaotic attractors
  • Fractal.py - Core fractal generation algorithms
  • components.py - UI components and rendering
  • finder_components.py - Chaos finder UI components
  • transform_components.py - Transformation system components
  • chaostech/ - Mathematical utilities and rule systems
  • docs/ - Documentation and test cases
  • requirements.txt - Python dependencies
  • runtime.txt - Python runtime version for Heroku
  • Procfile - Heroku deployment configuration

Features

The Python implementation includes:

  1. Chaos Game - Generate fractals like the Sierpinski triangle using the chaos game algorithm
  2. Iterated Function Systems (IFS) - Create complex fractals using transformation systems
  3. Automatic Chaos Finder - Automatically discover chaotic 2D discrete maps
  4. Multiple Fractal Types - Mandelbrot, Julia sets, Burning Ship, and more
  5. Interactive Parameters - Real-time parameter adjustment
  6. Preset Library - Pre-configured fractal parameters

Historical Context

This was the original implementation created for the MATH326 - Nonlinear Dynamics & Chaos course at McGill University (Fall 2021). The web application was deployed on Heroku and provided a full-featured fractal generation environment.

Performance Notes

The Python implementation, while feature-complete, has performance limitations:

  • Sierpinski Triangle: ~15,748 points/sec
  • Dragon Curve: ~30,675 points/sec
  • Mandelbrot Set: ~83,478 pixels/sec

For significantly improved performance, see the WebAssembly implementation in the root directory, which provides 10-100x faster rendering.

Running the Python Implementation

To run the original Python version:

cd python_implementation
pip install -r requirements.txt
python app.py

Then open http://localhost:5000 in your browser.

Migration to WebAssembly

This Python implementation serves as the reference for the new WebAssembly version. The algorithms and functionality are being ported to Rust/WebAssembly for dramatically improved performance while maintaining the same features and visual output.