💻 Algorithm Visualization Project: Divide and Conquer

This project provides graphical visualizations for two classic algorithms implemented using the Divide and Conquer paradigm:

• Karatsuba Multiplication Algorithm
• Closest Pair of Points Algorithm

The visualizations are built with Python, using matplotlib and networkx, with a GUI provided via tkinter for easy interaction and file selection.

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✨ Features

• Karatsuba Multiplication Visualization: Animates the recursive steps of the Karatsuba algorithm using a directed graph (tree) structure, showing the breakdown and recombination of the multiplication problem.

• Closest Pair of Points Visualization: Animates the divide and conquer process for finding the closest pair of points, including plane division and strip checking.

• GUI for Interaction: Simplifies generating random input files and selecting files for visualization.

• Random File Generation: RandomFile.py creates diverse input files for testing both algorithms.

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📂 Project Structure

├── Integer_Multiplication.py      # Karatsuba visualization
├── Closest_Pair.py               # Closest pair visualization
├── RandomFile.py                  # Generates random input files
├── README.md                      # Project documentation
└── RandomFiles/                   # Directory with generated input files

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🚀 Getting Started

Prerequisites

• Python 3.x installed
• Python libraries: matplotlib, networkx, pydot
• GraphViz command-line utility (for pydot layouts) – download from graphviz.org

Installation

1. Clone the repository

git clone https://github.com/YOUR_USERNAME/YOUR_REPO_NAME.git
cd YOUR_REPO_NAME

2. Install required Python libraries

pip install matplotlib networkx pydot

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⚙️ Usage

1. Generate Input Files

Use the “Generate Random Files” button in the GUI to create input files.

• Output directory: RandomFiles/
• Files:
  • integers_*.txt – for Karatsuba Multiplication
  • points_*.txt – for Closest Pair of Points

2. Run Visualization

Karatsuba Multiplication

python Integer_Multiplication.py

Closest Pair of Points

python Closest_Pair.py

Follow the GUI prompts to select files and view the animated visualizations.

🤝 Contributing

Contributions are welcome! Open an issue or submit a pull request.

📝 License

This project is licensed under the MIT License.