The freud Python package is a powerful 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. While many comparable tools place a heavy emphasis on reading and operating on trajectory file formats, freud instead accepts numerical arrays of data directly as inputs. By remaining agnostic to its data source, freud is suitable for analyzing any coarse-grained 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.

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弗洛伊德：用于粒子模拟数据高通量分析的软件套件

弗洛伊德 Python 包是一个强大的用于分析模拟数据的库。考虑到现代模拟和数据分析工作流程，弗洛伊德提供了一个 Python 接口，用于在笔记本电脑、工作站和超级计算集群上高效运行的快速并行 C++ 例程。该软件包提供了在周期系统中寻找粒子邻居的核心工具，并为使用这些工具实现的各种方法提供了统一的 API。因此，弗洛伊德用户可以同样轻松地访问标准方法，例如径向分布函数以及更新、更专业的方法，例如平均力和扭矩的潜力以及局部晶体环境分析。虽然许多类似的工具都非常强调读取和操作轨迹文件格式，相反，弗洛伊德直接接受数据的数值数组作为输入。通过对其数据源保持不可知，弗洛伊德适用于分析任何粗粒度粒子模拟，无论原始数据表示或模拟方法如何。当与 HOOMD-blue 等可编写脚本的模拟软件结合用于动态分析时，弗洛伊德可以实现适应系统当前状态的智能模拟，从而允许用户研究成核和生长等现象。