Post-processing tools for particle simulations
Project description
Python post processing tools to compute static and dynamic correlation functions from particle-based simulations. Supported correlation functions: - real space: radial distribution function, mean square displacement, time-dependent overlap, … - Fourier space: structure factor, intermediate scattering function, dynamic susceptibility, …
This package relies on atooms to read trajectory files.
Getting started
Post processing tools typically operate on trajectory files produced by molecular simulation codes. Any trajectory format recognized by atooms can be processed, for instance most “xyz” trajectory files should work fine. The correlation functions can be computed using either the command line script pp.py or directly from python.
Example: the following command will compute the radial distribution function g(r) from the trajectory file trajectory.xyz contained in the data/ directory
$ pp.py gr data/trajectory.xyz
The results will be stored in the file data/trajectory.xyz.pp.gr. If multiple chemical species are present, say A and B, the program will create additional files for partial correlations, named trajectory.xyz.pp.gr.A-A, trajectory.xyz.pp.gr.B-B and trajectory.xyz.pp.gr.A-B.
The same kind of calculation can be done from python:
from atooms.trajectory import Trajectory
import postprocessing as pp
with Trajectory('data/trajectory.xyz') as t:
p = pp.RadialDistributionFunction(t)
p.do()
See the tutorials under docs/ for more details.
Requirements
numpy
argh (optional, only needed when using pp.py)
Installation
From the code repository
git clone https://gitlab.info-ufr.univ-montp2.fr/atooms/postprocessing.git cd postprocessing make install
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