基于约束的图美化

Sitt Sen Chok, K. Marriott, Tom Paton
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引用次数: 21

摘要

最近出现了一种新的图解比喻——智能图。这个新的隐喻为图美化提供了一个很好的基础,因为它自动收集几何约束,在图构建过程中捕获图的语义。通过应用特定于可视化语言的布局规则,这些规则对图组件的放置施加了额外的期望约束,我们可以提供强大的保持语义的图美化。我们通过开发企鹅系统的简单扩展来证明这种方法的可行性,该系统从视觉语言的语法规范中生成美化规则,并使用三种示例视觉语言测试了该系统:二叉树,状态转移图和数学方程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Constraint-based diagram beautification
Recently a new metaphor for diagramming, the intelligent diagram has emerged. This new metaphor provides an excellent basis for diagram beautification since it automatically collects geometric constraints which capture the semantics of a diagram during diagram construction. By applying visual-language-specific layout rules which impose additional desired constraints on the diagram component placement, we can provide powerful semantics preserving diagram beautification. We have demonstrated the feasibility of this approach by developing a simple extension to the Penguins system which generates beautification rules from a grammatical specification of the visual language and tested the system with three example visual languages: Binary trees, state transition diagrams and mathematical equations.
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