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用于晶体学数据分析的Python库。

: a Python library for crystallographic data analysis.

作者信息

Greisman Jack B, Dalton Kevin M, Hekstra Doeke R

机构信息

Department of Molecular and Cellular Biology, Harvard University, 52 Oxford Street, Cambridge, MA 02138, USA.

John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.

出版信息

J Appl Crystallogr. 2021 Sep 4;54(Pt 5):1521-1529. doi: 10.1107/S160057672100755X. eCollection 2021 Oct 1.

Abstract

Crystallography uses the diffraction of X-rays, electrons or neutrons by crystals to provide invaluable data on the atomic structure of matter, from single atoms to ribosomes. Much of crystallography's success is due to the software packages developed to enable automated processing of diffraction data. However, the analysis of unconventional diffraction experiments can still pose significant challenges - many existing programs are closed source, sparsely documented, or challenging to integrate with modern libraries for scientific computing and machine learning. Described here is , a Python library for exploring reciprocal space. It provides a tabular representation for reflection data from diffraction experiments that extends the widely used library with built-in methods for handling space groups, unit cells and symmetry-based operations. As is illustrated, this library facilitates new modes of exploratory data analysis while supporting the prototyping, development and release of new methods.

摘要

晶体学利用晶体对X射线、电子或中子的衍射来提供有关物质原子结构的宝贵数据,范围从单个原子到核糖体。晶体学的许多成功都归功于为实现衍射数据自动处理而开发的软件包。然而,对非常规衍射实验的分析仍然可能带来重大挑战——许多现有程序是闭源的,文档稀少,或者难以与用于科学计算和机器学习的现代库集成。这里介绍的是一个用于探索倒易空间的Python库。它为衍射实验的反射数据提供了一种表格表示形式,扩展了广泛使用的库,并内置了处理空间群、晶胞和基于对称性的操作的方法。如图所示,该库有助于探索性数据分析的新模式,同时支持新方法的原型设计、开发和发布。

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