partycls: A Python package for structural clustering

TL;DR

partycls is a Python package that simplifies the process of clustering particles in systems based on structural or dynamical features, facilitating quick, unsupervised analysis in condensed matter physics.

Contribution

It introduces an easy-to-use Python framework that integrates descriptors, clustering, and analysis tools for particle system exploration.

Findings

Enables rapid clustering of particle systems with minimal code

Supports analysis of structural and dynamical properties

Streamlines workflow for condensed matter physics applications

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.