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包是一款面向模拟数据分析的专业工具库。该库以现代模拟与数据分析工作流为设计核心，为快速、并行化的C++运算例程提供Python接口，可在笔记本电脑、工作站乃至超级计算集群上高效运行。本库提供了周期性系统中粒子近邻查找的核心工具，并基于这些工具为众多分析方法提供了统一的应用程序编程接口（Application Programming Interface，API）。借此，freud用户可轻松调用各类分析手段：既涵盖径向分布函数（radial distribution function）等经典标准方法，也能便捷使用平均力势与力矩、局部晶体环境分析等新兴专业分析方法。freud并未自研轨迹数据结构，而是直接兼容NumPy数组，或是支持其他Python库提供的轨迹数据结构。此设计使得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。由于该库对数据源保持无偏向性，因此可适配任意粒子模拟的数据分析需求，不受原始数据表示形式或模拟方法的限制。当与HOOMD-blue等支持脚本化的模拟软件配合用于实时分析时，freud可驱动智能模拟系统根据当前系统状态自适应调整，帮助用户研究成核与生长等各类物理现象。