Jarvis-HEP

Just a Really Viable Interface to Suite for High Energy Physics.

Jarvis-HEP is a high-energy physics (HEP) data analysis and simulation framework developed in Python, designed to simplify the process of data handling and analysis for researchers and students in the field of particle physics.

Features

• Supports various sampling methods, enabling comprehensive parameter space exploration.
• Integrated with popular HEP computational modules and libraries for seamless analysis workflows.
• Asynchronous and parallel computing support for optimized performance on large datasets.
• Data management and storage solutions tailored for high-volume data processing, including input/output handling and database integration.

Installation

Jarvis-HEP is a pure Python code, using pip install the following package:

python3 -m pip install numpy scipy pyyaml dynesty h5py pandas matplotlib pyhf networkx xslha pyslha xmltodict shapely emoji prettytable aiofiles sqlalchemy loguru 

Clone Jarvis-HEP directly from GitHub:

git clone https://github.com/Pengxuan-Zhu-Phys/Jarvis-HEP.git

Contributing

Contributions are welcome in all forms, including feature proposals, documentation improvements, bug reports, and bug fixes. Please refer to CONTRIBUTING.md for guidelines on how to get started.

License

Jarvis-HEP is released under the MIT license. For more details, see the LICENSE file.

Acknowledgements

Special thanks to all contributors who have helped make this project possible. Pengxuan thank Yang Zhang, Liangliang Shang for helpful discussion.