Metadata-Version: 2.1
Name: mddatasetbuilder
Version: 1.2.0
Summary: A script to make molecular dynamics (MD) datasets for neural networks from given LAMMPS trajectories automatically.
Home-page: https://github.com/njzjz/mddatasetbuilder
Author: Jinzhe Zeng
Author-email: jzzeng@stu.ecnu.edu.cn
License: UNKNOWN
Description: # MDDatasetBuilder
        
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        MDDatasetBuilder is a script to build molecular dynamics (MD) datasets for neural networks from given LAMMPS trajectories automatically.
        
        **Author**: Jinzhe Zeng
        
        **Email**: jzzeng@stu.ecnu.edu.cn
        
        [![Research Group](https://img.shields.io/website-up-down-green-red/http/computchem.cn.svg?label=Research%20Group)](http://computchem.cn)
        
        ## Requirements
        * Python 3.6 - 3.7
        * Python packages:
        [numpy](https://github.com/numpy/numpy),
        [scikit-learn](https://github.com/scikit-learn/scikit-learn),
        [ASE](https://gitlab.com/ase/ase),
        [GaussianRunner](https://github.com/njzjz/gaussianrunner),
        [tqdm](https://github.com/tqdm/tqdm),
        [coloredlogs](https://github.com/xolox/python-coloredlogs),
        [lz4](https://github.com/python-lz4/python-lz4),
        [pybase64](https://github.com/mayeut/pybase64)
        * Software:
        [Gaussian 16](http://gaussian.com/),
        [DeePMD](https://github.com/deepmodeling/deepmd-kit)
        
        ## Installation
        
        ```sh
        git clone https://github.com/njzjz/mddatasetbuilder
        cd mddatasetbuilder
        pip install .
        ```
        
        You can test whether ReacNetGenerator is running normally:
        ```sh
        python3 setup.py pytest
        ```
        
        ## Simple example
        
        A [LAMMPS bond file](http://lammps.sandia.gov/doc/fix_reax_bonds.html) and a [LAMMPS dump file](https://lammps.sandia.gov/doc/dump.html) should be prepared.
        
        ```bash
        datasetbuilder -d dump.ch4 -b bonds.reaxc.ch4_new -a C H O -n ch4 -i 25
        ```
        
        Then you can calculate generated Gaussian files:
        
        ```bash
        qmcalc -d dataset_ch4_GJf/000
        qmcalc -d dataset_ch4_GJf/001
        ```
        
        Next, prepare DeePMD datas and use [DeePMD-kit](https://github.com/deepmodeling/deepmd-kit) to train a model.
        
        ```bash
        preparedeepmd -p dataset_ch4_GJf -a C H O
        cd train && dp_train train.json
        ```
        
Keywords: molecular dynamics dataset
Platform: UNKNOWN
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Version Control :: Git
Requires-Python: ~=3.6
Description-Content-Type: text/markdown
Provides-Extra: test
