Sliceplorer: 1D slices for multi-dimensional continuous functions

Sliceplorer: 1D slices for multi-dimensional continuous functions

Abstract

Multi-dimensional continuous functions are commonly visualized with 2D slices or topological views. Here, we explore 1D slices as an alternative approach to show such functions. Our goal with 1D slices is to combine the benefits of topological views, that is, screen space efficiency, with those of slices, that is a close resemblance of the underlying function. We compare 1D slices to 2D slices and topological views, first, by looking at their performance with respect to common function analysis tasks. We also demonstrate 3 usage scenarios: the 2D sinc function, neural network regression, and optimization traces. Based on this evaluation, we characterize the advantages and drawbacks of each of these three approaches, and show how interaction can be used to overcome some of the shortcomings.

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Authors
  • Torsney-Weir, Thomas
  • Sedlmair, Michael
  • Möller, Torsten
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Supplemental Material

UNSPECIFIED

Shortfacts
Category
Journal Paper
Divisions
Visualization and Data Analysis
Journal or Publication Title
Eurographics + EG EuroVis // Computer Graphics Forum: (Journal of the Eurographics Association)
ISSN
0167-7055
Page Range
PREPRINT
Date
2017
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