Radial Level Planarity Testing and Embedding in Linear Time
Christian Bachmaier,Franz-Josef Brandenburg,Michael Forster +2 more
- pp 393-405
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TLDR
Radial planarity as mentioned in this paper is a generalisation of level planarity, where the vertices are placed on k horizontal lines and the edges are routed as curves without crossings, and it is decidable in linear time.Abstract:
Every planar graph has a concentric representation based on a breadth first search, see [21]. The vertices are placed on concentric circles and the edges are routed as curves without crossings. Here we take the opposite view. A graph with a given partitioning of its vertices onto k concentric circles is k-radial planar, if the edges can be routed monotonic between the circles without crossings. Radial planarity is a generalisation of level planarity, where the vertices are placed on k horizontal lines. We extend the technique for level planarity testing of [18,17,15,16,12,13] and show that radial planarity is decidable in linear time, and that a radial planar embedding can be computed in linear time.read more
Citations
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Journal ArticleDOI
Upper Bounds for Monotone Planar Circuit Value and Variants
TL;DR: Cylindricality is characterized, which is stronger than planarity but strictly generalizes upward planarity, and made the characterization partially constructive, and it is shown that monotone circuits with toroidal embeddings can, given such an embedding, be evaluated in NC.
Book ChapterDOI
Evaluating monotone circuits on cylinders, planes and tori
TL;DR: In this article, the authors revisited monotone planar circuits MPCVP with cylindrical embeddings, and showed that these circuits can be evaluated in LogDCFL, AC1(LogDCFL), LogCFL and AC 1(LogCFL) respectively.
Posted Content
Toward the Hanani-Tutte Theorem for Clustered Graphs
TL;DR: The weak variant of the weak Hanani-Tutte theorem for strip-clustered planar graphs was shown to imply the monotone variant of weak HNT by Pach and Toth as mentioned in this paper.
Journal ArticleDOI
Computing Radial Drawings on the Minimum Number of Circles
TL;DR: In this paper, the problem of computing radial drawings of planar graphs by using the minimum number of concentric circles was studied, and it was proven that the problem can be solved in polynomial time.
Circle Planarity of Level Graphs
TL;DR: The main results are linear time algorithms both for the planarity test and for the computation of an embedding, and thus a drawing, which use and generalise PQ-trees, which are a data structure for efficient planarity tests.
References
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Book
Graph Drawing: Algorithms for the Visualization of Graphs
TL;DR: In this paper, the authors describe fundamental algorithmic techniques for constructing drawings of graphs and provide an accurate, accessible reflection of the rapidly expanding field of graph drawing, using a reference manual.
Journal ArticleDOI
Testing for the consecutive ones property, interval graphs, and graph planarity using PQ-tree algorithms
TL;DR: The consecutive ones test for the consecutive ones property in matrices and for graph planarity is extended to a test for interval graphs using a recently discovered fast recognition algorithm for chordal graphs.
Journal ArticleDOI
Methods for Visual Understanding of Hierarchical System Structures
TL;DR: Two kinds of new methods are developed to obtain effective representations of hierarchies automatically: theoretical and heuristic methods that determine the positions of vertices in two steps to improve the readability of drawings.
LEDA, a Platform for Combinatorial and Geometric Computing.
TL;DR: There is no standard library of the data structures and algorithms of combinatorial and geometric computing as mentioned in this paper, which is in sharp contrast to many other areas of computing, such as discrete optimization, scheduling, traffic control, CAD, and graphics.
Book
LEDA: A Platform for Combinatorial and Geometric Computing
Kurt Mehlhorn,Stefan Näher +1 more
TL;DR: There is no standard library of the data structures and algorithms of combinatorial and geometric computing as discussed by the authors, which is in sharp contrast to many other areas of computing, such as discrete optimization, scheduling, traffic control, CAD, and graphics.
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