A VENUS96 trajectory converter
Author: mizu-bai
- Python 3.8 and above
- Numpy
venus-trjconv
can convert VENUS96 trajectories to gro
, g96
, and xyz
format, making it easier to visualize and analyze the trajectories calculated by VENUS96.
$ python3 -m venus_trjconv -h
usage: venus_trjconv [-h] -f F [-s S] [-o O] [-dt DT] [-r R]
Convert VENUS96 trajectory to other formats.
optional arguments:
-h, --help show this help message and exit
-f F Trajectory: VENUS96 output
-s S Structure: gro xyz
-o O Trajectory: gro g96 xyz
-dt DT Only write frame when t MOD dt = first time (ps)
-r R Reorder file
In folder example/
, there is a QCT trajectory of methane molecule.
ch4.dt5
: VENUS96 input file.ch4.out
: VENUS96 output file, containing 5 trajectories.template.gro
: Gro file,venus_trjconv
will read the title, number of atoms, residue numbers, residue names, atom names, atom numbers and box size stored in it.template.xyz
: XYZ file,venus_trjconv
will read the title, number of atoms stored in it.reorder.txt
: In VENUS96 output, the order of atoms isH H H H C
, while it is supposed to beC H H H H
in converted trajectories. Thus, a reorder file should be supplied. In thereorder.txt
file, the first line is5
, indicating that the 5th atom (C
) in VENUS96 output should be the 1st atom in converted trajectories. If the order of atoms in the VENUS96 output is correct, the reorder file and-r
option are not necessary.
Convert to gro
$ python3 -m venus_trjconv -f ch4.out -s template.gro -o gro/ch4_traj.gro -r reorder.txt
Convert to g96
$ python3 -m venus_trjconv -f ch4.out -o g96/ch4_traj.g96 -r reorder.txt
Convert to xyz
$ python3 -m venus_trjconv -f ch4.out -s template.xyz -o xyz/ch4_traj.xyz -r reorder.txt
(1) Hase, W. L.; Duchovic, R. J.; Hu, X.; Komornicki, A.; Lim, K. F.; Lu, D.-H.; Peslherbe, G. H.; Swamy, K. N.; Vande Linde, S. R.; Varandas, A., Wang, H.; Wolf, R. J. VENUS96: A general chemical dynamics computer program, Quantum Chemical Program Exchange (QCPE) Bulletin, 1996, 16 (4), 671. https://www.depts.ttu.edu/chemistry/Venus/index.php
(2) Abraham, M. J.; Murtola, T.; Schulz, R.; Páll, S.; Smith, J. C.; Hess, B.; Lindahl, E. GROMACS: High Performance Molecular Simulations through Multi-Level Parallelism from Laptops to Supercomputers. SoftwareX 2015, 1–2, 19–25. https://doi.org/10.1016/j.softx.2015.06.001.
(3) Scott, W. R. P.; Hünenberger, P. H.; Tironi, I. G.; Mark, A. E.; Billeter, S. R.; Fennen, J.; Torda, A. E.; Huber, T.; Krüger, P.; van Gunsteren, W. F. The GROMOS Biomolecular Simulation Program Package. J. Phys. Chem. A 1999, 103 (19), 3596–3607. https://doi.org/10.1021/jp984217f.
BSD-2-Clause license