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引用次数: 0
摘要
该导览为探索高维数据集提供了一个有用的工具。它的工作原理是将一系列投影(游览路径)与动画(显示方法)相结合。当前R中的显示实现在交互性和可移植性方面受到限制,即使对于小数据集,也会给出较差的性能和不稳定的动画。我们绕道进入web技术,如Three.js和WebGL,以支持流畅和高性能的旅游可视化。R包实现了一组显示工具,允许丰富的交互(包括轨道控制、擦除和刷刷)和大型数据集的平滑动画。它提供了一个新用户可以访问的声明式R接口,并且它支持使用串扰和闪亮的链接视图。生成的动画可以在各种浏览器和设备上移植。我们还将Sage Tour (@laa2021burning)的径向变换扩展到三维或三维以上,并提供了Slice Tour (@laa2020slice)的简化实现。
Taking the Scenic Route: Interactive and Performant Tour Animations
The tour provides a useful vehicle for exploring high dimensional datasets. It works by combining a sequence of projections---the tour path---in to an animation---the display method. Current display implementations in R are limited in their interactivity and portability, and give poor performance and jerky animations even for small datasets. We take a detour into web technologies, such as Three.js and WebGL, to support smooth and performant tour visualisations. The R package detourr implements a set of display tools that allow for rich interactions (including orbit controls, scrubbing, and brushing) and smooth animations for large datasets. It provides a declarative R interface which is accessible to new users, and it supports linked views using crosstalk and shiny. The resulting animations are portable across a wide range of browsers and devices. We also extend the radial transformation of the Sage Tour (@laa2021burning) to 3 or more dimensions with an implementation in 3D, and provide a simplified implementation of the Slice Tour (@laa2020slice).
R JournalCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
2.70
自引率
0.00%
发文量
40
审稿时长
>12 weeks
期刊介绍:
The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R.
The R Journal intends to reach a wide audience and have a thorough review process. Papers are expected to be reasonably short, clearly written, not too technical, and of course focused on R. Authors of refereed articles should take care to:
- put their contribution in context, in particular discuss related R functions or packages;
- explain the motivation for their contribution;
- provide code examples that are reproducible.