TensorView for MATLAB: Visualizing tensors with Euler angle decoding

IF 1.8 3区化学 Q4 CHEMISTRY, PHYSICAL Solid state nuclear magnetic resonance Pub Date : 2023-02-01 DOI:10.1016/j.ssnmr.2022.101849

Leo Svenningsson , Leonard J. Mueller

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引用次数: 1

Abstract

TensorView for MATLAB is a GUI-based visualization tool for depicting second-rank Cartesian tensors as surfaces on three-dimensional molecular models. Both ellipsoid and ovaloid tensor display formats are supported, and the software allows for easy conversion of Euler angles from common rotation schemes (active, passive, ZXZ, and ZYZ conventions) with visual feedback. In addition, the software displays all four orientation-equivalent Euler angle solutions for the placement of a single tensor in the molecular frame and can report relative orientations of two tensors with all 16 orientation-equivalent Euler angle sets that relate them. The salient relations are derived and illustrated through several examples. TensorView for MATLAB expands and complements the earlier implementation of TensorView within the Mathematica programming environment and can be run without a MATLAB license. TensorView for MATLAB is available through github at https://github.com/LeoSvenningsson/TensorViewforMatlab, and can also be accessed directly via the NMRbox resource.

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TensorView for MATLAB:可视化张量与欧拉角解码

TensorView for MATLAB是一个基于GUI的可视化工具，用于将二阶笛卡尔张量描述为三维分子模型上的曲面。支持椭球和椭圆张量显示格式，该软件允许通过视觉反馈轻松转换常见旋转方案（主动、被动、ZXZ和ZYZ约定）的欧拉角。此外，该软件显示了在分子框架中放置单个张量的所有四个方向等效欧拉角解，并可以报告两个张量的相对方向以及与它们相关的所有16个方向等效的欧拉角集。通过几个例子推导和说明了显著的关系。TensorView for MATLAB扩展并补充了早期在Mathematica编程环境中实现的TensorView，并且可以在没有MATLAB许可证的情况下运行。用于MATLAB的TensorView可通过github获得，网址为https://github.com/LeoSvenningsson/TensorViewforMatlab，也可以通过NMRbox资源直接访问。

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来源期刊

Solid state nuclear magnetic resonance 物理-光谱学

CiteScore

5.30

自引率

9.40%

发文量

审稿时长

72 days

期刊介绍： The journal Solid State Nuclear Magnetic Resonance publishes original manuscripts of high scientific quality dealing with all experimental and theoretical aspects of solid state NMR. This includes advances in instrumentation, development of new experimental techniques and methodology, new theoretical insights, new data processing and simulation methods, and original applications of established or novel methods to scientific problems.