Tehrani Alireza, Yang Xiaotian Derrick, Martínez-González Marco, Pujal Leila, Hernández-Esparza Raymundo, Chan Matthew, Vöhringer-Martinez Esteban, Verstraelen Toon, Ayers Paul W, Heidar-Zadeh Farnaz
Department of Chemistry, Queen's University, Kingston, Ontario K7L-3N6, Canada.
Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S-4L8, Canada.
J Chem Phys. 2024 May 7;160(17). doi: 10.1063/5.0202240.
Grid is a free and open-source Python library for constructing numerical grids to integrate, interpolate, and differentiate functions (e.g., molecular properties), with a strong emphasis on facilitating these operations in computational chemistry and conceptual density functional theory. Although designed, maintained, and released as a stand-alone Python library, Grid was originally developed for molecular integration, interpolation, and solving the Poisson equation in the HORTON and ChemTools packages. Grid is designed to be easy to use, extend, and maintain; this is why we use Python and adopt many principles of modern software development, including comprehensive documentation, extensive testing, continuous integration/delivery protocols, and package management. We leverage popular scientific packages, such as NumPy and SciPy, to ensure high efficiency and optimized performance in grid development. This article is the official release note of the Grid library showcasing its unique functionality and scope.
Grid是一个免费的开源Python库,用于构建数值网格以对函数(例如分子性质)进行积分、插值和求导,特别侧重于在计算化学和概念密度泛函理论中方便地进行这些操作。尽管Grid作为一个独立的Python库进行设计、维护和发布,但它最初是为HORTON和ChemTools包中的分子积分、插值以及求解泊松方程而开发的。Grid的设计目标是易于使用、扩展和维护;这就是我们使用Python并采用许多现代软件开发原则的原因,包括全面的文档、广泛的测试、持续集成/交付协议以及包管理。我们利用诸如NumPy和SciPy等流行的科学包,以确保在网格开发中实现高效率和优化性能。本文是Grid库的官方发布说明,展示了其独特的功能和范围。