Permutation exists in various domains such as mathematics, combinatorics, and computer science. Enumerating each permutation, as well as the multivariate information among different items, allows us, for example, to observe distribution, similarity, and dissimilarity of all possible permutations and select a satisfactory permutation or solution. However, the number of permutations increases dramatically along with the number of items in the permutation, which makes it challenging for users to evaluate potential solutions and identify interesting insights. In this paper, we propose PermVizor, a novel and scalable visualization system that aims assisting users exploring the arrangement, distribution, and comparison of permutations. Necessary and comprehensive analysis of requirements is presented for visualization of permutations. PermVizor enables users to explore overall distribution of each permutation with a glyph-based MDS view, investigate statistical information of selected permutations with a parallel coordinates view, and examine detailed arrangement of the items as well the multivariate information among them for each permutation with pixel-based and block-based PermView. Case studies are conducted on classical datasets such as the axis reordering issue in parallel coordinate data and permutation of traveling salesman problem, which shows that PermVizor could facilitate users in exploring unexpected and desired permutations and confirm their finding and decisions in expected permutations.
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This work is partly supported by National Natural Science Foundation of China (No. 61972356), Zhejiang Provincial Natural Science Foundation of China (No. LY19F020026), National Natural Science Foundation of China (No. 61602409), Zhejiang Povincial Key Research and Development Program of China No. 2019C01009), and Fundamental Research Funds for the Provincial Universities of Zhejiang (No. RF-C2019001).
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Sun, G., Zhou, Z., Chang, B. et al. PermVizor: visual analysis of multivariate permutations. J Vis 22, 1225–1240 (2019). https://doi.org/10.1007/s12650-019-00599-w
- Multi-dimensional data
- Parallel coordinate