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Welcome to the home page of the reForge Python package.
Overview of reForge Package
The reForge source code is hosted on GitHub at: https://github.com/DanYev/reforge
The reForge Python package offers a set of tools for MD simulations, analysis, and data processing. It includes optimized mathematical routines, GPU-accelerated computations, and various helper tools to make simulation setup and data handling easier. Created to aid advanced research in simulation and analysis, reForge is available to the public under the GNU V3 License.
What’s in reForge?
Here are the main features of reForge:
Python package for Molecular Dynamics: Provides easy-to-use workflows for setting up, running, and analyzing MD simulations of large biomolecular systems.
User-friendly Interface: Designed to be accessible for both beginners and advanced users, making it easier to manage numerous MD simulations. Check out some basic workflows here: workflows.
Optimized Mathematical Routines: Utilizes GPU and Cython acceleration to speed up analysis tasks, significantly reducing computation times.
For New Users
Learn the Basics: Familiarize yourself with the basics of shell scripting, SLURM, git, and Python.
Understand the Fundamentals: Get a grasp of object-oriented programming and high-performance computing concepts to make the most of reForge’s capabilities.
Explore the Documentation: Skim through the available documentation and examples provided within the package to learn about the various tools and workflows.
For Developers
contribution guidelines: if you plan to contribute to reForge, please refer to the developer documentation for coding standards, testing procedures, and version control guidelines.
testing and documentation: an extensive suite of tests and detailed documentation accompanies the package to ensure reliability and maintainability.
community and support: contributions are welcome! please check the github repository for issues, feature requests, and further discussion.
Acknowledgements
The reForge package is maintained by ****. This project is inspired by and builds upon multiple excellent open-source packages such as Cython, NumPy, CuPy, GROMACS, OpenMM, Vermouth and MDAnalysis.