Metadata-Version: 2.1
Name: mdapy
Version: 0.9.9
Summary: A simple, fast and cross-platform python library to handle the data generated from molecular dynamics simulations.
Home-page: https://github.com/mushroomfire/mdapy
Author: mushroomfire aka HerrWu
Author-email: yongchao_wu@bit.edu.cn
License: BSD 3-Clause License
Project-URL: Homepage, https://github.com/mushroomfire/mdapy
Project-URL: Documentation, https://mdapy.readthedocs.io/
Project-URL: Issue Tracker, https://github.com/mushroomfire/mdapy/issues
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Requires-Python: >=3.8,<3.12
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: taichi >=1.6.0
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: polars >=0.19.14
Requires-Dist: matplotlib
Provides-Extra: all
Requires-Dist: k3d ; extra == 'all'
Requires-Dist: tqdm ; extra == 'all'
Requires-Dist: pyfftw ; extra == 'all'
Provides-Extra: k3d
Requires-Dist: k3d ; extra == 'k3d'
Provides-Extra: pyfftw
Requires-Dist: pyfftw ; extra == 'pyfftw'
Provides-Extra: tqdm
Requires-Dist: tqdm ; extra == 'tqdm'

.. image:: https://img.pterclub.com/images/2023/01/06/logo.png

*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 <https://github.com/taichi-dev/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 <https://www.lammps.org/>`_, POSCAR format in `VASP <https://www.vasp.at/wiki/index.php/The_VASP_Manual>`_, and universal XYZ format. Besides, all data in **mdapy** is stored in NDARRAY format in `NumPy <https://numpy.org/>`_\ , which enables easy integration 
with the scientific ecosystem in python and facilitates collaboration with other post-progressing 
tools such as `OVITO <https://www.ovito.org/>`_ and `freud <https://github.com/glotzerlab/freud>`_.

Resources
----------

- Homepage: `https://github.com/mushroomfire/mdapy <https://github.com/mushroomfire/mdapy>`_
- Documentation: `https://mdapy.readthedocs.io/ <https://mdapy.readthedocs.io/>`_
- Issue Tracker: `https://github.com/mushroomfire/mdapy/issues <https://github.com/mushroomfire/mdapy/issues>`_

