mdapy : Molecular Dynamics Analysis with Python

Overview

The mdapy python library provides an array of powerful, flexible, and straightforward tools to analyze atomic trajectories generated from Molecular Dynamics (MD) simulations. The library is fully cross-platform, making it accessible to users in Windows, Linux, and Mac OS. Benefited by the TaiChi project, we can effectively accelerate the pure python code, bringing it closer to the speed of code written in C++. Furthermore, mdapy is highly parallelized, allowing users to leverage the resources of both multicore CPU and GPU. mdapy can directly handle the DUMP and DATA formats in LAMMPS, POSCAR format in VASP, universal XYZ format and CIF format. Besides, all data in mdapy is stored in NDARRAY format in NumPy, which enables easy integration with the scientific ecosystem in python and facilitates collaboration with other post-progressing tools such as OVITO and freud.

Resources

Dependencies

Optional Dependencies

  • k3d (Optional, for visualizing the 3D atoms.)

  • tqdm (Optional, for progress bar when reading/saving multi files)

  • pyfftw (Optional, for fast FFT)

Citation

If you find mdapy useful, you can star it! If you use mdapy in your scientific publications, please cite the paper:

@article{mdapy2023,
   title = {mdapy: A flexible and efficient analysis software for molecular dynamics simulations},
   journal = {Computer Physics Communications},
   pages = {108764},
   year = {2023},
   issn = {0010-4655},
   doi = {https://doi.org/10.1016/j.cpc.2023.108764},
   url = {https://www.sciencedirect.com/science/article/pii/S0010465523001091},
   author = {Yong-Chao Wu and Jian-Li Shao},
   keywords = {Simulation analysis, Molecular dynamics, Polycrystal, TaiChi, Parallel computing}
   }

Getting Started

Mdapy Python API