A comprehensive collection of Python applications and Jupyter notebooks for simulating self-affine fractals, combining mathematical visualization, interactive applications, and scientific documentation to explore fractal geometry.

Interactive React Apps: https://tyson-swetnam.github.io/fractal-notebooks/react

Documentation: https://tyson-swetnam.github.io/fractal-notebooks

• Interactive Streamlit Applications - Real-time fractal visualization with parameter controls
• Jupyter Notebooks - Educational content with mathematical theory and implementations
• Research-Grade Tools - Scientific Python stack for fractal analysis and dimension calculation
• Comprehensive Documentation - MkDocs site with LaTeX equations and theory
• Cloud Deployment - K3s Kubernetes with GPU support for scalable computation
• Containerization - Docker deployment for consistent environments

• apps/ - Streamlit applications for interactive fractal visualization
• docs/ - MkDocs documentation with mathematical content and theory
• docs/notebooks/ - Jupyter notebooks with fractal algorithms and examples
• k3s-deployment/ - Kubernetes configurations for JupyterLab and Weaviate
• docker/ - Docker containerization for Streamlit applications
• react/ - React-based web applications for fractal exploration

git clone https://github.com/tyson-swetnam/fractal-notebooks.git
cd fractal-notebooks
pip install -r requirements.txt
python -m mkdocs serve

Access at http://localhost:8000

# Run specific applications
streamlit run apps/mandelbrot.py
streamlit run apps/branching_tree.py
streamlit run apps/julia.py

cd docker/
docker build -t fractal-app .
docker run -p 8501:8501 fractal-app

kubectl create namespace ai-workloads
kubectl apply -f k3s-deployment/ -n ai-workloads

• Documentation: MkDocs with Material theme, MathJax for equations
• Interactive Apps: Streamlit for web-based fractal visualizations
• Notebooks: Jupyter with NumPy, Matplotlib, SciPy scientific stack
• Deployment: K3s Kubernetes with GPU support for AI workloads
• Containerization: Docker for application packaging and deployment

• Mandelbrot & Julia Sets: Complex number iterations
• Barnsley Ferns: Iterated function systems
• Tree Structures: L-systems and branching patterns
• Noise Generation: Brownian motion and pink noise simulations

• Differential Box Counting: Fractal dimension analysis
• Dimensionality Studies: Mathematical analysis of fractal properties
• 3D Visualizations: Interactive Plotly and Matplotlib rendering

Contributions are welcome! Please see individual folder README files for specific development guidelines:

• apps/README.md - Streamlit application development
• docs/README.md - Documentation structure and MkDocs configuration
• k3s-deployment/README.md - Kubernetes deployment guide

If you use this work in your research, please cite:

@misc{fractal-notebooks,
  title={Fractal Notebooks: Interactive Platform for Self-Affine Fractal Analysis},
  author={Swetnam, Tyson},
  year={2024},
  url={https://github.com/tyson-swetnam/fractal-notebooks}
}

This project is open source and available under the MIT License.