https://github.com/njzjz/kconmd

Molecular dynamics (MD) simulations supported by k-Bags Convolutional Neural Network (kcon).
https://github.com/njzjz/kconmd

chemistry convolutional-neural-network deep-learning molecular-dynamics python3 tensorflow

Last synced: over 1 year ago
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Molecular dynamics (MD) simulations supported by k-Bags Convolutional Neural Network (kcon).

• Host: GitHub
• URL: https://github.com/njzjz/kconmd
• Owner: njzjz
• Created: 2018-07-18T14:44:46.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2024-07-07T21:56:28.000Z (almost 2 years ago)
• Last Synced: 2025-03-18T04:12:35.728Z (over 1 year ago)
• Topics: chemistry, convolutional-neural-network, deep-learning, molecular-dynamics, python3, tensorflow
• Language: Python
• Size: 5.16 MB
• Stars: 3
• Watchers: 2
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: docs/README.md

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README

          
# kconMD (k-Bags Convolutional Neural Network Molecular Dynamics)

[![python version](https://img.shields.io/pypi/pyversions/kconmd.svg?logo=python&logoColor=white)](https://pypi.org/project/kconmd)

[![PyPI](https://img.shields.io/pypi/v/kconmd.svg)](https://pypi.org/project/kconmd)

[![Build Status](https://travis-ci.com/njzjz/kconmd.svg?branch=master)](https://travis-ci.com/njzjz/kconmd)

[![Coverage Status](https://coveralls.io/repos/github/njzjz/kconmd/badge.svg?branch=master)](https://coveralls.io/github/njzjz/kconmd?branch=master)

[![codecov](https://codecov.io/gh/njzjz/kconmd/branch/master/graph/badge.svg)](https://codecov.io/gh/njzjz/kconmd)

Molecular Dynamics (MD) simulations supported by [k-Bags Convolutional Neural Network (kCON)](https://github.com/njzjz/kcon).

**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://computechem.cn)

## Acknowledgement

Many thanks to [Xin Chen](https://github.com/Bismarrck) for his help and development of [kCON](https://github.com/Bismarrck/kcon).

## Requirements

* [numpy](https://github.com/numpy/numpy)

* [scipy](https://github.com/scipy/scipy)

* [matplotlib](https://github.com/matplotlib/matplotlib)

* [scikit-learn](https://github.com/scikit-learn/scikit-learn)

* [ASE](https://wiki.fysik.dtu.dk/ase/)

* [TensorFlow](https://github.com/tensorflow/tensorflow)

## Installation

### With pip

```sh

pip install kconmd

```

### Build from source

```sh

$ git clone https://github.com/njzjz/kconmd

$ cd kconmd/

$ pip install .

```

## Examples

### Simple example

See [examples/example.py](examples/example.py).

### Client–server model

See [examples/server.py](examples/server.py) and [examples/client.py](examples/client.py).

### Run MD with LAMMPS

See [njzjz/Pyforce](https://github.com/njzjz/Pyforce) repository and install Pyforce module. Then rename [examples/client.py](examples/client.py) as `force.py` and put it where you run LAMMPS. Add a line in the LAMMPS input file:

```

fix 1 all pyforce C H O

```