freud: A software suite for high throughput analysis of particle simulation data

The freud Python package is a library for analyzing simulation data. Written with modern simulation and data analysis workflows in mind, freud provides a Python interface to fast, parallelized C++ routines that run efficiently on laptops, workstations, and supercomputing clusters. The package provides the core tools for finding particle neighbors in periodic systems, and offers a uniform API to a wide variety of methods implemented using these tools. As such, freud users can access standard methods such as the radial distribution function as well as newer, more specialized methods such as the potential of mean force and torque and local crystal environment analysis with equal ease. Rather than providing its own trajectory data structure, freud operates either directly on NumPy arrays or on trajectory data structures provided by other Python packages. This design allows freud to transparently interface with many trajectory file formats by leveraging the file parsing abilities of other trajectory management tools. By remaining agnostic to its data source, freud is suitable for analyzing any particle simulation, regardless of the original data representation or simulation method. When used for on-the-fly analysis in conjunction with scriptable simulation software such as HOOMD-blue, freud enables smart simulations that adapt to the current state of the system, allowing users to study phenomena such as nucleation and growth.freud Python包是一款用于分析模拟数据的专业库。本库秉持现代模拟与数据分析工作流的设计理念，为快速、并行化的C++核心例程提供Python调用接口，可在笔记本电脑、工作站及超级计算集群上高效运行。该库提供了周期性系统中粒子近邻识别的核心工具，并基于此类工具为各类分析方法提供统一应用程序编程接口（API）。因此，freud用户可轻松调用两类分析手段：既包含径向分布函数等经典标准方法，也涵盖平均力势与力矩、局部晶体环境分析等新型专业分析技术。freud并未自研轨迹数据结构，而是支持直接操作NumPy数组，或兼容其他Python库提供的轨迹数据结构。该设计使得freud可借助其他轨迹管理工具的文件解析能力，无缝适配多种轨迹文件格式。由于freud不对数据源做特定限制，因此可适用于任意粒子模拟的数据分析，无需考虑原始数据的表示形式或模拟方法本身。当与HOOMD-blue等可脚本化模拟软件配合用于实时在线分析时，freud可实现适配系统当前状态的智能模拟，助力用户研究成核、生长等物理现象。