Reaction Network Generator
Project description
ReacNetGenerator
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
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
Installation
You can install Anaconda or Miniconda to obtain conda, and install ReacNetGenerator easily with conda:
conda install reacnetgenerator -c conda-forge
See the build guide if you want to build ReacNetGenerator by yourself.
Usage
Command line
ReacNetGenerator can process any kind of trajectory files containing atomic coordinates, e.g. a LAMMPS dump file prepared by running “dump 1 all custom 100 dump.reaxc id type x y z” in LAMMPS:
reacnetgenerator --dump -i dump.reaxc -a C H O
where C, H, and O are atomic names in the input file. Analysis report will be generated automatically.
Also, ReacNetGenerator can process files containing bond information, e.g. LAMMPS bond file:
reacnetgenerator -i bonds.reaxc -a C H O
You can running the following script for help:
reacnetgenerator -h
GUI version
You can open a GUI version for ReacNetGenerator by typing:
reacnetgeneratorgui
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)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
Hashes for reacnetgenerator-1.4.112-cp38-cp38-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 66798663a8fe65a0abe0096fe374731e7a3d54efb42ed65a96a308ca8aa7acbf |
|
MD5 | b4360a83ec4664d70805c846213caf34 |
|
BLAKE2b-256 | 62579190fd7c86c14162424dab327deaf42e3bc1396b7ab31264b445f5e468ce |
Hashes for reacnetgenerator-1.4.112-cp38-cp38-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0f97fbe6040c0125d95cf269afe428582072bc94f66fa6968eec01c23bffe1e5 |
|
MD5 | f5e658be1cd48657f4e6f99ac7f85393 |
|
BLAKE2b-256 | 300e2cd6af1bcb7ba2ce38db6fe74970d85c0bd20f6d8ae340d7c3207ebdbc0b |
Hashes for reacnetgenerator-1.4.112-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7819faafacfbecf6eedf406a47c9f91e87c89b09004210d4e1afd756bdfd5e31 |
|
MD5 | 4912c55b2a91add2f055af5f9cce007e |
|
BLAKE2b-256 | ad3ded20859e2c4ddc4c836184f6565ba31e3ea5cced713bab3a7946924ceefb |
Hashes for reacnetgenerator-1.4.112-cp37-cp37m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9aa903abe4f07316827e7a10d3c27f519dbf64d4aaf180ead0b07cb07c876868 |
|
MD5 | 31a0688424a5dd3c36a862ea736147ed |
|
BLAKE2b-256 | a49c81a79fc3d4a7f3bb4ab7a79d87943732a2890bc85b2c40ffcd1612221e59 |
Hashes for reacnetgenerator-1.4.112-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8302a763aac69e30e64f9512c1c2f31c33ae66d1034f72abbec241dbcb6f6023 |
|
MD5 | edb2bf1f4f11d717275438c97ae6147c |
|
BLAKE2b-256 | d75fff273139185256fe1075840bd524762443d1410be3d71a92d8c02fa77e7c |
Hashes for reacnetgenerator-1.4.112-cp36-cp36m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 03bd90547852dc6a9e7fae0cc793277f608df207cbca187d702cbf3d8ae7529b |
|
MD5 | 6be7a38c554d7d113f1d900c3a3e944f |
|
BLAKE2b-256 | a0d05b7a109167de41afa50a0ada7afe83773f2046bc1334cff5901c012f542e |