Tutorial: Analysis#
In this tutorial, we analyze a simple trajectroy as an example. The trajectory is taken from the real case the thermal decomposition of CL-20.
Download this trajectory using wget
:
%%bash
wget https://raw.githubusercontent.com/tongzhugroup/TRAJREAX/f10a5c2cab77d3f3b659d9dd08256ae7b27c2820/cl20/cl20.lammpstrj -O cl20.lammpstrj
--2022-11-05 08:51:40-- https://raw.githubusercontent.com/tongzhugroup/TRAJREAX/f10a5c2cab77d3f3b659d9dd08256ae7b27c2820/cl20/cl20.lammpstrj
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.110.133, 185.199.111.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 920127 (899K) [text/plain]
Saving to: ‘cl20.lammpstrj’
0K .......... .......... .......... .......... .......... 5% 4.24M 0s
50K .......... .......... .......... .......... .......... 11% 5.15M 0s
100K .......... .......... .......... .......... .......... 16% 24.7M 0s
150K .......... .......... .......... .......... .......... 22% 20.2M 0s
200K .......... .......... .......... .......... .......... 27% 7.99M 0s
250K .......... .......... .......... .......... .......... 33% 42.7M 0s
300K .......... .......... .......... .......... .......... 38% 38.7M 0s
350K .......... .......... .......... .......... .......... 44% 40.9M 0s
400K .......... .......... .......... .......... .......... 50% 54.6M 0s
450K .......... .......... .......... .......... .......... 55% 58.8M 0s
500K .......... .......... .......... .......... .......... 61% 9.66M 0s
550K .......... .......... .......... .......... .......... 66% 45.7M 0s
600K .......... .......... .......... .......... .......... 72% 38.5M 0s
650K .......... .......... .......... .......... .......... 77% 80.2M 0s
700K .......... .......... .......... .......... .......... 83% 70.4M 0s
750K .......... .......... .......... .......... .......... 89% 68.7M 0s
800K .......... .......... .......... .......... .......... 94% 67.0M 0s
850K .......... .......... .......... .......... ........ 100% 79.9M=0.05s
2022-11-05 08:51:41 (18.5 MB/s) - ‘cl20.lammpstrj’ saved [920127/920127]
Then use reacnetgenerator
to analyze it. Note the order of elements (H C N O
) MUST map to those in the trajectory.
%%bash
reacnetgenerator -i cl20.lammpstrj -a H C N O --type dump --nohmm
2022-11-05 08:51:46,154 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: ReacNetGenerator: an automatic reaction network generator for reactive
molecular dynamics simulation.
Please cite: 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 (jinzhe.zeng@rutgers.edu), Tong Zhu (tzhu@lps.ecnu.edu.cn)
==================
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
==================
Simple example
==================
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 --type dump -i dump.reaxc -a C H O --nohmm
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 --type bond -i bonds.reaxc -a C H O --nohmm
You can running the following script for help:
$ reacnetgenerator -h
2022-11-05 08:51:46,154 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Version: 1.6.6.dev24+g068dac4 Creation date: 2018-03-11
Read bond information and Detect molecules: 0timestep [00:00, ?timestep/s]
Read bond information and Detect molecules: 2timestep [00:01, 1.40timestep/s]
Read bond information and Detect molecules: 101timestep [00:01, 70.84timestep/s]
Save molecules: 0%| | 0/11 [00:00<?, ?molecule/s]
Save molecules: 100%|██████████| 11/11 [00:00<00:00, 3376.31molecule/s]
2022-11-05 08:51:47,881 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Step 1: Done! Time consumed (s): 1.726 (Read bond information and detect molecules)
2022-11-05 08:51:47,941 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Step 2: Done! Time consumed (s): 0.060 (Merge isomers)
HMM filter: 0molecule [00:00, ?molecule/s]
HMM filter: 11molecule [00:00, 2628.61molecule/s]
2022-11-05 08:51:48,139 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Step 3: Done! Time consumed (s): 0.198 (HMM filter)
Indentify isomers: 0%| | 0/11 [00:00<?, ?molecule/s]
Indentify isomers: 100%|██████████| 11/11 [00:00<00:00, 585.62molecule/s]
Analyze atoms: 0%| | 0/11 [00:00<?, ?molecule/s]
Analyze atoms: 100%|██████████| 11/11 [00:00<00:00, 7775.08molecule/s]
Collect reaction paths: 0%| | 0/288 [00:00<?, ?atom/s]
Collect reaction paths: 100%|██████████| 288/288 [00:00<00:00, 11114.42atom/s]
Analyze reactions (A+B->C+D): 0%| | 0/100 [00:00<?, ?timestep/s]
Analyze reactions (A+B->C+D): 100%|██████████| 100/100 [00:00<00:00, 12790.24timestep/s]
2022-11-05 08:51:48,583 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Step 4: Done! Time consumed (s): 0.444 (Indentify isomers and collect reaction paths)
2022-11-05 08:51:48,651 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Step 5: Done! Time consumed (s): 0.068 (Reaction matrix generation)
2022-11-05 08:51:48,667 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Species are:
2022-11-05 08:51:48,667 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: 1 [H]C12N(N(=O)=O)C3([H])N(N(=O)=O)C1([H])N(N(=O)=O)C1([H])N(N(=O)=O)C3([H])N(N(=O)=O)C1([H])N2N(=O)=O
2022-11-05 08:51:48,667 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: 2 [H]C12NC3([H])N(N(=O)=O)C1([H])N(N(=O)=O)C1([H])N(N(=O)=O)C3([H])N(N(=O)=O)C1([H])N2N(=O)=O
2022-11-05 08:51:48,667 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: 3 O=NO
2022-11-05 08:51:48,672 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: The position of the species in the network is:
2022-11-05 08:51:48,672 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: {1: array([-5.95629110e-05, -1.00129074e-04]), 2: array([-0.59480018, -0.99989987]), 3: array([0.59485974, 1. ])}
2022-11-05 08:51:48,855 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Step 6: Done! Time consumed (s): 0.204 (Draw reaction network)
2022-11-05 08:51:48,878 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Report is generated. Please see cl20.lammpstrj.html for more details.
2022-11-05 08:51:48,942 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Step 7: Done! Time consumed (s): 0.087 (Generate analysis report)
2022-11-05 08:51:48,942 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: ====== Summary ======
2022-11-05 08:51:48,942 - ReacNetGenerator 1.6.6.dev24+g068dac4 - INFO: Total time(s): 2.787 s
The results are shown in cl20.lammpstrj.html
. In addition, we can view an overview of reactions in the trajectory in the command line:
%%bash
cat cl20.lammpstrj.reactionabcd
1 [H]C12N(N(=O)=O)C3([H])N(N(=O)=O)C1([H])N(N(=O)=O)C1([H])N(N(=O)=O)C3([H])N(N(=O)=O)C1([H])N2N(=O)=O->O=NO+[H]C12NC3([H])N(N(=O)=O)C1([H])N(N(=O)=O)C1([H])N(N(=O)=O)C3([H])N(N(=O)=O)C1([H])N2N(=O)=O
Here we can clearly see that the CL-20 molecule is decomposited into a nitrogen dioxide molecule.