atooms-pp 4.2.1

Post-processing tools for particle simulations

Postprocessing

A Python package to compute static and dynamic correlation functions from simulations of interacting particles, such as molecular dynamics or Monte Carlo simulations. Based on atooms.

Quick start

Postprocessing works on trajectories. Any trajectory format recognized by atooms can be processed, for instance most "xyz" files should work fine. If you use a custom trajectory format, it is easy to add it.

As an example, we compute the structure factor S(k) from the file trajectory.xyz in the data/ folder.

From the command line

pp.py --norigins 0.2 msd data/trajectory.xyz

We just used 20% of the available time frames to compute the averages using the --norigins flag. Without it, atooms-pp applies an heuristics to determine the number of time frames required to achieve a reasonable data quality. The results of the calculation are stored in the file data/trajectory.xyz.pp.sk.

From Python

The same calculation can be done from Python:

from atooms.trajectory import Trajectory
import atooms.postprocessing as pp

with Trajectory('data/trajectory.xyz') as t:
     p = pp.StructureFactor(t)
     p.do()

Features

Available correlation and distribution functions

• Real space
  • radial distribution function
  • mean square displacement
  • velocity auto-correlation function
  • self overlap functions
  • collective overlap functions
  • dynamic susceptibility of the self overlap function
  • non-Gaussian parameter
  • bond-angle distribution
  • self van Hove distribution function
  • distinct van Hove distribution function
  • orientational time-dependent correlation functions
  • orientation-angle distribution
• Fourier space
  • structure factor
  • spectral density
  • self intermediate scattering functions
  • collective intermediate scattering functions
  • four-point dynamic susceptibility

Most correlation functions admits a center-of-mass variant suitable for the molecular centers of mass.

Documentation

Check out the tutorial for more examples and the public API for full details.

Org-mode and jupyter notebooks are available under docs/. You can run the tutorial interactively on Binder.

Installation

Install with pip

pip install atooms-pp

Or clone the project repository

git clone https://framagit.org/atooms/postprocessing.git
cd postprocessing
make install

Contributing

Contributions to the project are welcome. If you wish to contribute, check out these guidelines.

Authors

Daniele Coslovich: https://www.units.it/daniele.coslovich/