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-1.4.122-cp38-cp38-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b63e1c7861338f689b81807c158a466fb6e863af44a676e0db1c9515b874507b |
|
MD5 | d6df226efffd818f882eb110a8c56ded |
|
BLAKE2b-256 | f6e86e4c8ca109bdde5afa6fa3006659b3a58a6111f67e8e511a3f761f976acc |
Hashes for reacnetgenerator-1.4.122-cp38-cp38-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | ae1116cd48e484ab399d85021c82fda4cf2bc4488b86ac7985e4cbc18558baab |
|
MD5 | adc219e5d375d4f1089334c0fd513aa5 |
|
BLAKE2b-256 | bb8bb3bf21d830c97a9bb189b2cf7971a820a482c4556e0f33d4946ba214514e |
Hashes for reacnetgenerator-1.4.122-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | eca8108633b3f33b46cc4d4d01f910c000dab8599124f15ca8d128e79e022249 |
|
MD5 | 24c869f60d9417b4a1fdda4e75d82d45 |
|
BLAKE2b-256 | 1502632ad819f9d74bea04c8c747d78ba4025a5d24b2c3b6b8f753c9cda2f8a5 |
Hashes for reacnetgenerator-1.4.122-cp37-cp37m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | a031006849608021f06da8d34e3d02309bb825fb7d9fb635a5b4c9639803b660 |
|
MD5 | 0177dcdf6e57e3406bb41add04bcfb86 |
|
BLAKE2b-256 | 0966cbfd930ffbc0d07d3e73d8ae286aae5e27c4439818aa16b5786875518f7c |
Hashes for reacnetgenerator-1.4.122-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 056dbc3aa804352ab98f01fea8559ecb2e76061f20e00d251e998c5eba41ccb7 |
|
MD5 | 2ad157efe1d1444f69fe4ac414205401 |
|
BLAKE2b-256 | cb6187549e392decf67a962c01581fab396cf6012713503a1e7788433677a496 |
Hashes for reacnetgenerator-1.4.122-cp36-cp36m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 95169b810680cfbe3aae39a1c76f1ed001f5f35c7b069580bcc47c772d92ac3d |
|
MD5 | b589d02f9a71b6a66930314e2fd269c4 |
|
BLAKE2b-256 | 34d46806a526b26fd4484372297801eace14f4f8936e1ff4768a4ca518382085 |