reacnetgenerator
所属分类:人工智能/神经网络/深度学习
开发工具:Python
文件大小:0KB
下载次数:0
上传日期:2024-03-04 08:26:10
上 传 者:
sh-1993
说明: 用于 React分子动力学模拟的自动 React网络发生器
(an automatic reaction network generator for reactive molecular dynamics simulation)
文件列表:
conda/recipe/
docs/
reacnetgenerator/
tests/
.license-header.txt
.pre-commit-config.yaml
CITATION.cff
Dockerfile
LICENSE
codecov.yml
pyproject.toml
renovate.json
setup.py
tox.ini
#
ReacNetGenerator
[![DOI:10.1039/C9CP05091D](https://img.shields.io/badge/DOI-10.1039%2FC9CP05091D-blue)](https://doi.org/10.1039/C9CP05091D)
[![Citations](https://citations.njzjz.win/10.1039/C9CP05091D)](https://doi.org/10.1039/C9CP05091D)
[![Research Group](https://img.shields.io/website-up-down-green-red/https/computchem.cn.svg?label=Research%20Group)](https://computchem.cn)
An automatic reaction network generator for reactive molecular dynamics simulation.
ReacNetGenerator: an automatic reaction network generator for reactive molecular dynamic simulations, Phys. Chem. Chem. Phys., 2020, 22 (2): 683–691, doi: [10.1039/C9CP05091D](https://dx.doi.org/10.1039/C9CP05091D)
jinzhe.zeng@rutgers.edu (Jinzhe Zeng), tzhu@lps.ecnu.edu.cn (Tong Zhu)
## Features
- Processing of MD trajectory containing atomic coordinates or bond orders
- Hidden Markov Model (HMM) based noise filtering
- Isomers identifying accoarding to SMILES
- Generation of reaction network for visualization using force-directed algorithm
- Parallel computing
## Guide and Tutorial
The latest version requires Python 3.7 or later.
You can install ReacNetGenerator with `conda`:
```sh
conda install reacnetgenerator -c conda-forge
reacnetgenerator -h
```
See [the guide](https://reacnetgenerator.njzjz.win/guide/) to learn how to install and use ReacNetGenerattor. We also provide [a series of tutorials](https://reacnetgenerator.njzjz.win/tutorial/) to help you learn ReacNetGenerator.
## Awards
* The First Prize in 2019 (the 11th Session) Shanghai Computer Application Competition for College Students
* The First Prize in 2019 (the 12th Session) Chinese Computer Design Competition for College Students
## Acknowledge
* National Natural Science Foundation of China (Grants No. 91641116)
* National Innovation and Entrepreneurship Training Program for Undergraduate (201910269080)
* ECNU Multifunctional Platform for Innovation (No. 001)
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