AMEP: The Active Matter Evaluation Package for Python

• Published in: Computer physics communications 2025-04, Vol.309, p.109483, Article 109483
• Main Authors: Hecht, Lukas, Dormann, Kay-Robert, Spanheimer, Kai Luca, Ebrahimi, Mahdieh, Cordts, Malte, Mandal, Suvendu, Mukhopadhyay, Aritra K., Liebchen, Benno
• Format: Article
• Language: English
• ISSN: 0010-4655
• DOI: 10.1016/j.cpc.2024.109483

The Active Matter Evaluation Package (AMEP) is a Python library for analyzing simulation data of particle-based and continuum simulations. It provides a powerful and simple interface for handling large data sets and for calculating and visualizing a broad variety of observables that are relevant to active matter systems. Examples range from the mean-square displacement and the structure factor to cluster-size distributions, binder cumulants, and growth exponents. AMEP is written in pure Python and is based on powerful libraries such as NumPy, SciPy, Matplotlib, and scikit-image. Computationally expensive methods are parallelized and optimized to run efficiently on workstations, laptops, and high-performance computing architectures, and an HDF5-based data format is used in the backend to store and handle simulation data as well as analysis results. AMEP provides the first comprehensive framework for analyzing simulation results of both particle-based and continuum simulations (as well as experimental data) of active matter systems. In particular, AMEP also allows it to analyze simulations that combine particle-based and continuum techniques such as used to study the motion of bacteria in chemical fields or for modelling particle motion in a flow field for example. Program Title: Active Matter Evaluation Package (AMEP) CPC Library link to program files:https://doi.org/10.17632/zc7pn23g5r.1 Developer's repository link:https://github.com/amepproject/amep Licensing provisions: GPLv3 Programming language: Python Supplementary material: The supplementary material includes Movies S1–S3. Nature of problem: To date, no comprehensive package for analyzing data from simulations of active matter systems is available. Thus, most research groups in the fields of soft and active matter physics use in-house code to analyze their simulations, which means that often a significant part of the time that is available to students and advanced researchers for performing research projects is spent with the development of data-analysis and visualization software, at the expense of their research time budget. In practice, students (and advanced researchers) might sometimes even be forced to limit their data analysis to a few observables. The availability of a unified framework to rapidly determine a broad variety of key observables that are frequently used to analyze the structure and dynamics of active matter systems from raw particle-based or continuum-based simulation data would