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 modeling particle motion in a flow field for example. Program summary 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 therefore be highly beneficial for the research field. Solution method: AMEP provides the first unified framework for analyzing both particle-based and continuum simulation data. It performs a huge variety of analysis for both data types and uses a unified HDF5-based data format for efficient data handling. Since AMEP is written purely in Python and uses powerful libraries such as NumPy, SciPy, Matplotlib, and scikit-image commonly used in computational physics, understanding, modifying, and building up on the provided framework is comparatively easy. Compared to other analysis libraries, the huge variety of analysis methods combined with the possibility to handle common data types used in soft-matter physics and in the active matter community in particular, enables the analysis of a much broader class of simulation data. This includes not only classical molecular-dynamics or Brownian-dynamics simulations but also any kind of numerical solutions of partial differential equations. Additional comments including restrictions and unusual features: This paper serves as the definitive reference for AMEP. The source code and the documentation are available online at https://github.com/amepproject/amep and https://amepproject.de, respectively. AMEP may be installed via pip install amep or via conda install conda-forge::amep.
