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partycls: A Python package for structural clustering

Paret, Joris
•
Coslovich, Daniele
2021
  • journal article

Periodico
JOURNAL OF OPEN SOURCE SOFTWARE
Abstract
partycls is a Python framework for cluster analysis of systems of interacting particles. By grouping particles that share similar structural or dynamical properties, partycls enables rapid and unsupervised exploration of the system’s relevant features. It provides descriptors suitable for applications in condensed matter physics and integrates the necessary tools of unsupervised learning, such as dimensionality reduction, into a streamlined workflow. Through a simple and expressive interface, partycls allows one to open a trajectory file, perform a clustering based on the selected structural descriptor, and analyze and save the results with only a few lines of code.
DOI
10.21105/joss.03723
Archivio
http://hdl.handle.net/11368/2998765
https://joss.theoj.org/papers/10.21105/joss.03723
Diritti
open access
license:creative commons
license uri:http://creativecommons.org/licenses/by/4.0/
FVG url
https://arts.units.it/bitstream/11368/2998765/1/10.21105.joss.03723.pdf
Soggetti
  • python

  • machine learning

  • clustering

  • molecular dynamics

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