Computing cartograms with optimal complexity

Md Jawaherul Alam, Therese Biedl, Stefan Felsner, Michael Kaufmann, Stephen G Kobourov, Torsten Ueckerdt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

In a rectilinear dual of a planar graph vertices are represented by simple rectilinear polygons, while edges are represented by side-contact between the corresponding polygons. A rectilinear dual is called a cartogram if the area of each region is equal to a pre-specified weight. The complexity of a cartogram is determined by the maximum number of corners (or sides) required for any polygon. In a series of papers the polygonal complexity of such representations for maximal planar graphs has been reduced from the initial 40 to 34, then to 12 and very recently to the currently best known 10. Here we describe a construction with 8-sided polygons, which is optimal in terms of polygonal complexity as 8-sided polygons are sometimes necessary. Specifically, we show how to compute the combinatorial structure and how to refine it into an area-universal rectangular layout in linear time. The exact cartogram can be computed from the area-universal layout with numerical iteration, or can be approximated with a hill-climbing heuristic. We also describe an alternative construction of cartograms for Hamiltonian maximal planar graphs, which allows us to directly compute the cartograms in linear time. Moreover, we prove that even for Hamiltonian graphs 8-sided rectilinear polygons are necessary, by constructing a non-trivial lower bound example. The complexity of the cartograms can be reduced to 6 if the Hamiltonian path has the extra property that it is one-legged, as in outer-planar graphs. Thus, we have optimal representations (in terms of both polygonal complexity and running time) for Hamiltonian maximal planar and maximal outer-planar graphs.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual Symposium on Computational Geometry
Pages21-30
Number of pages10
DOIs
StatePublished - 2012
Event28th Annual Symposuim on Computational Geometry, SCG 2012 - Chapel Hill, NC, United States
Duration: Jun 17 2012Jun 20 2012

Other

Other28th Annual Symposuim on Computational Geometry, SCG 2012
CountryUnited States
CityChapel Hill, NC
Period6/17/126/20/12

Fingerprint

Hamiltonians
Planar graph
Polygon
Computing
Linear Time
Layout
Hamiltonian Graph
Hill Climbing
Hamiltonian path
Simple Polygon
Necessary
Heuristics
Contact
Lower bound
Iteration
Series
Alternatives

Keywords

  • Cartograms
  • Contact graphs
  • Geometric representations
  • Planar graphs

ASJC Scopus subject areas

  • Computational Mathematics
  • Geometry and Topology
  • Theoretical Computer Science

Cite this

Alam, M. J., Biedl, T., Felsner, S., Kaufmann, M., Kobourov, S. G., & Ueckerdt, T. (2012). Computing cartograms with optimal complexity. In Proceedings of the Annual Symposium on Computational Geometry (pp. 21-30) https://doi.org/10.1145/2261250.2261254

Computing cartograms with optimal complexity. / Alam, Md Jawaherul; Biedl, Therese; Felsner, Stefan; Kaufmann, Michael; Kobourov, Stephen G; Ueckerdt, Torsten.

Proceedings of the Annual Symposium on Computational Geometry. 2012. p. 21-30.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alam, MJ, Biedl, T, Felsner, S, Kaufmann, M, Kobourov, SG & Ueckerdt, T 2012, Computing cartograms with optimal complexity. in Proceedings of the Annual Symposium on Computational Geometry. pp. 21-30, 28th Annual Symposuim on Computational Geometry, SCG 2012, Chapel Hill, NC, United States, 6/17/12. https://doi.org/10.1145/2261250.2261254
Alam MJ, Biedl T, Felsner S, Kaufmann M, Kobourov SG, Ueckerdt T. Computing cartograms with optimal complexity. In Proceedings of the Annual Symposium on Computational Geometry. 2012. p. 21-30 https://doi.org/10.1145/2261250.2261254
Alam, Md Jawaherul ; Biedl, Therese ; Felsner, Stefan ; Kaufmann, Michael ; Kobourov, Stephen G ; Ueckerdt, Torsten. / Computing cartograms with optimal complexity. Proceedings of the Annual Symposium on Computational Geometry. 2012. pp. 21-30
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