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        "description": "# MDDatasetBuilder\n\n[![python version](https://img.shields.io/pypi/pyversions/mddatasetbuilder.svg?logo=python&logoColor=white)](https://pypi.org/project/mddatasetbuilder)\n[![PyPI](https://img.shields.io/pypi/v/mddatasetbuilder.svg)](https://pypi.org/project/mddatasetbuilder)\n[![Build Status](https://travis-ci.com/njzjz/mddatasetbuilder.svg?branch=master)](https://travis-ci.com/njzjz/mddatasetbuilder)\n[![Coverage Status](https://coveralls.io/repos/github/njzjz/mddatasetbuilder/badge.svg?branch=master)](https://coveralls.io/github/njzjz/mddatasetbuilder?branch=master)\n[![codecov](https://codecov.io/gh/njzjz/mddatasetbuilder/branch/master/graph/badge.svg)](https://codecov.io/gh/njzjz/mddatasetbuilder)\n[![Codacy Badge](https://api.codacy.com/project/badge/Grade/924ce85b916040079fb453785ec673f9)](https://www.codacy.com/app/jzzeng/mddatasetbuilder?utm_source=github.com&utm_medium=referral&utm_content=njzjz/mddatasetbuilder&utm_campaign=Badge_Grade)\n\nMDDatasetBuilder is a script to build molecular dynamics (MD) datasets for neural networks from given LAMMPS trajectories automatically.\n\n**Author**: Jinzhe Zeng\n\n**Email**: jzzeng@stu.ecnu.edu.cn\n\n[![Research Group](https://img.shields.io/website-up-down-green-red/http/computchem.cn.svg?label=Research%20Group)](http://computchem.cn)\n\n## Requirements\n* Python 3.6 - 3.7\n* Python packages:\n[numpy](https://github.com/numpy/numpy),\n[scikit-learn](https://github.com/scikit-learn/scikit-learn),\n[ASE](https://gitlab.com/ase/ase),\n[GaussianRunner](https://github.com/njzjz/gaussianrunner),\n[tqdm](https://github.com/tqdm/tqdm),\n[coloredlogs](https://github.com/xolox/python-coloredlogs),\n[lz4](https://github.com/python-lz4/python-lz4),\n[pybase64](https://github.com/mayeut/pybase64)\n* Software:\n[Gaussian 16](http://gaussian.com/),\n[DeePMD](https://github.com/deepmodeling/deepmd-kit),\n[OpenBabel](https://github.com/openbabel/openbabel)\n\n## Installation\n\n```sh\ngit clone https://github.com/njzjz/mddatasetbuilder\ncd mddatasetbuilder\npip install .\n```\n\nYou can test whether ReacNetGenerator is running normally:\n```sh\npython3 setup.py pytest\n```\n\n## Simple example\n\nA [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.\n\n```bash\ndatasetbuilder -d dump.ch4 -b bonds.reaxc.ch4_new -a C H O -n ch4 -i 25\n```\n\nThen you can calculate generated Gaussian files:\n\n```bash\nqmcalc -d dataset_ch4_GJf/000\nqmcalc -d dataset_ch4_GJf/001\n```\n\nNext, prepare DeePMD datas and use [DeePMD-kit](https://github.com/deepmodeling/deepmd-kit) to train a model.\n\n```bash\npreparedeepmd -p dataset_ch4_GJf -a C H O\ncd train && dp_train train.json\n```",
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