A simple and fast python library to handle the data generated from molecular dynamics simulations
Project description
mdapy : Molecular Dynamics Analysis with Python
Overview
The mdapy is a python library providing a set of simple, flexible and powerful tools to analyze the atomic trajectories generated from Molecular Dynamics (MD) simulations. Benefit by the TaiChi project, we can effectively accelerate the pure python code close to those written in C++. Moreover, mdapy is highly parallelized to make full use of resources of both multicore CPU and GPU. mdapy can directly handle the DUMP and DATA format in LAMMPS. All data in mdapy is stored in NDARRAY format in NumPy, enabling integration with the scientific ecosystem in python and corporation with other post-progressing codes, such as OVITO and freud.
Resources
Homepage: https://github.com/mushroomfire/mdapy
Documentation: https://mdapy.readthedocs.io/
Issue Tracker: https://github.com/mushroomfire/mdapy/issues
Dependencies
python (3.7-3.10)
Optional Dependencies
SciencePlots (Optional, for plotting results)
pyfftw (Optional, for fast FFT)
pyfnntw>=0.4.1 (Optional, for fast KNN search)
Installation
Install from pip (recommended).
pip install mdapy
Install from source code.
You should install pybind11 and have a C++ compilation environment.
pip install pybind11
Download source code
git clone https://github.com/mushroomfire/mdapy.git cd mdapy python setup.py install
Usage
import mdapy as mp
mp.init('cpu') # use cpu, mp.init('gpu') will use gpu to compute.
system = mp.System('./example/CoCuFeNiPd-4M.dump') # read dump file to generate a system class
system.cal_centro_symmetry_parameter() # calculate the centrosymmetry parameters
system.cal_atomic_entropy() # calculate the atomic entropy
system.write_dump() # save results to a new dump file
Main Features
Structure Analysis
Potential Analysis
Melting Analysis
Geometry Structure Creation
Neighbor Search
Other
Citation
If you find mdapy useful, you can start it! If you use mdapy in your scientific publication, because the paper is under review on Computer Physics Communication and you can cite its preprint version as below:
Wu, Yong-Chao and Shao, Jian-Li, Mdapy: A Flexible and Efficient Analysis Software for
Molecular Dynamics Simulations. Available at SSRN: https://ssrn.com/abstract=4360931
or http://dx.doi.org/10.2139/ssrn.4360931.
Trouble Shoot
If you encounter ImportError in Linux:
version 'GLIBCXX_3.4.29' not found.
You can try:
conda install -c conda-forge gxx_linux-64
Release Notes
V0.8.1
Add Steinhardt Bondorder Parameter method, which can be used to identify the lattice structure and distinguish the solid/liquid phase during melting process.
Add Polyhedral Template Mathing method.
Add IdentifySFsTBs method to identify the stacking faults (SFs) and twinning boundary (TBs) in FCC lattice.
V0.8.0
Add Ackland Jones Analysis (AJA) method.
Add Common Neighbor Parameter (CNP) method.
Update the nearest neighbor search in CSP method.
V0.7.9
Fix bug of create_polycrystalline module in Linux.
V0.7.8
Update TaiChi version to 1.4.0.
Set SciencePlots as a optional package.
Fix bug in create_polycrystalline.
Project details
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