🧮 CVLA: Complex Visualizer and Linear Algebra

An AI-powered educational platform that transforms abstract mathematical concepts into interactive, visual experiences.

✨ Overview

CVLA revolutionizes the way students and educators approach Complex Variables and Linear Algebra. Through cutting-edge visualizations and AI-enhanced computation, we make complex mathematical concepts intuitive and engaging.

🚀 Features

🎨 Complex Function Visualization

Experience the beauty of complex analysis through domain coloring techniques that reveal the intricate behavior of complex functions.

🔄 Matrix Transformations

Explore linear transformations in both 2D and 3D spaces with real-time visual feedback and interactive controls.

🎯 Eigenvalue & Eigenvector Exploration

Dive deep into matrix properties with dynamic visualizations of eigenspaces and characteristic behaviors.

📐 Inner Product Visualization

Understand geometric interpretations of inner products through interactive visual representations.

🌟 Quick Start

Prerequisites

• Python 3.8 or higher
• pip package manager

Installation

# Clone the repository
git clone https://github.com/divyanshupatel17/complex-visualizer.git
cd complex-visualizer

# Install dependencies
pip install -r requirements.txt

# Launch the application
streamlit run app.py

Your browser will automatically open to http://localhost:8501 where you can start exploring!

🎯 Usage

1. Launch the app using the installation steps above
2. Select a topic from the sidebar navigation
3. Interact with visualizations using the provided controls
4. Experiment with parameters to see real-time changes
5. Learn through exploration with our guided examples

🛠️ Tech Stack

• Frontend: Streamlit
• Visualization: Matplotlib, Plotly
• Computation: NumPy, SciPy
• AI Integration: Custom mathematical algorithms

📱 Live Demo

Experience CVLA without any setup required:

🚀 Try CVLA Now

🤝 Contributing

We welcome contributions! Here's how you can help:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📧 Contact

Divyanshu Patel
📧 itzdivyanshupatel@gmail.com

📄 License

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

🙏 Acknowledgments

• Our amazing contributors and community members
• Educational institutions supporting open-source learning tools
• The Python scientific computing ecosystem

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Made with ❤️ for mathematical education

⭐ Star this project if it helped you learn!