Comet-Path-Detection 🌠

A Python-based project for detecting and tracking comet paths using advanced astronomical algorithms and data processing techniques.

📋 Overview

This repository contains tools and utilities for analyzing celestial observations and identifying comet trajectories. The project combines computational astronomy with machine learning approaches to detect and predict comet paths with high accuracy.

🌟 Features

• Comet Detection: Automated detection of comet signatures in astronomical data
• Path Tracking: Real-time tracking of comet trajectories
• Data Analysis: Comprehensive analysis tools for astronomical observations
• Visualization: Advanced plotting and visualization capabilities
• Docker Support: Containerized deployment for easy setup and reproducibility

🛠 Tech Stack

• Python (98.3%) - Core implementation
• Docker (1.7%) - Containerization

📦 Installation

Using Docker

docker build -t comet-path-detection .
docker run -it comet-path-detection

Local Setup

1. Clone the repository:

git clone https://github.com/Yash200691/Comet-Path-Detection.git
cd Comet-Path-Detection

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

🚀 Quick Start

# Example usage
from comet_detection import CometDetector

detector = CometDetector()
results = detector.detect_comet_paths(data_file='observations.csv')
detector.visualize_results(results)

📊 Project Structure

Comet-Path-Detection/
├── README.md
├── Dockerfile
├── requirements.txt
├── src/
│   ├── __init__.py
│   ├── detection/
│   ├── tracking/
│   └── visualization/
├── tests/
└── data/
    └── sample_observations/

🔬 Usage

Detection Mode

python -m comet_detection detect --input observations.csv --output results.json

Visualization

python -m comet_detection visualize --data results.json --output plots/

📚 Documentation

For detailed documentation, see:

• CONTRIBUTING.md - Contribution guidelines
• API Reference - Complete API documentation
• Examples - Usage examples and tutorials

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

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

📝 License

This project is open source and available under the MIT License. See the LICENSE file for more details.

📮 Contact & Support

For questions, issues, or suggestions:

• Open an Issue
• Reach out to @Yash200691

🙏 Acknowledgments

• Astronomical data sources and references
• Contributors and collaborators
• Community feedback and support

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Happy comet hunting! 🌌