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 Distributions
Built Distributions
Hashes for reacnetgenerator-1.4.110-cp38-cp38-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0ceabcc54ca0218081b629dd5a5a5c594c213ad8f7e9648ddbcdcc5589a12852 |
|
MD5 | 706186dcf3e1d3c83e425dcc4dcf46ca |
|
BLAKE2b-256 | c95fd1ccbd058c3b7b6d70ab45ecf389a78a9d7bf34cfe6242e2074fa0d5a51f |
Hashes for reacnetgenerator-1.4.110-cp38-cp38-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 59e96fe6b8836fa3562b1fbc1be8f2e420492843ebd7d44669f6965596f06687 |
|
MD5 | 33a27a904631693dcdaa23830e0303cf |
|
BLAKE2b-256 | 149c7d2ee962417955572202135c77ed3fdedafcc3a35ef4df6c5d59cf950c7e |
Hashes for reacnetgenerator-1.4.110-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 88ec9ba409447fdbea70f5858e336ba11df28916f8a337a75c5a11a7940c7bf2 |
|
MD5 | b4f6396dbe9f9a9fff5e8894421a240a |
|
BLAKE2b-256 | b23203204aa8b427483f58e05e17bd4f175b03800aeef20bdd69e4103b0c8a75 |
Hashes for reacnetgenerator-1.4.110-cp37-cp37m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 56bfc14314e44bc340c90c120258786bccbc2ea942ebbdf1acdd194d4b98490f |
|
MD5 | a078716a9a790913b8ac66f918421745 |
|
BLAKE2b-256 | 47e9a707ea4b5938bfe7fda17e8a3bd4d3fa75a84f13a0f999b09f2bccabfb77 |
Hashes for reacnetgenerator-1.4.110-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5442f6176d50702cc1d349e8e5baa12a5062c50c87bbbca94e1ae083f5d53797 |
|
MD5 | adcabbfbdc7a98d3e855d0fe94d7bdaf |
|
BLAKE2b-256 | 264336c084d76418a7b9f054e1441c980f5d634e73cb1d09554708fe74c4d9e0 |
Hashes for reacnetgenerator-1.4.110-cp36-cp36m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 83eef8f03c6f0f5ad58640d983b3af463a0a4e0f40da8f3c4d523010bae0e30e |
|
MD5 | c0ed0ebd8ae977e697ca94f0382f158a |
|
BLAKE2b-256 | 79974b57ed70492827f147f056d2226704f897da4f03a67c35f439a83aa2767d |