46 research outputs found

    Two-Page Book Embeddings of 4-Planar Graphs

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    Back in the Eighties, Heath showed that every 3-planar graph is subhamiltonian and asked whether this result can be extended to a class of graphs of degree greater than three. In this paper we affirmatively answer this question for the class of 4-planar graphs. Our contribution consists of two algorithms: The first one is limited to triconnected graphs, but runs in linear time and uses existing methods for computing hamiltonian cycles in planar graphs. The second one, which solves the general case of the problem, is a quadratic-time algorithm based on the book-embedding viewpoint of the problem.Comment: 21 pages, 16 Figures. A shorter version is to appear at STACS 201

    Drawing Clustered Graphs as Topographic Maps

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    The visualization of clustered graphs is an essential tool for the analysis of networks, in particular, social networks, in which clustering techniques like community detection can reveal various structural properties. In this paper, we show how clustered graphs can be drawn as topographic maps, a type of map easily understandable by users not familiar with information visu- alization. Elevation levels of connected entities correspond to the nested structure of the cluster hierarchy. We present methods for initial node placement and describe a tree mapping based algorithm that produces an area efficient layout. Given this layout, a triangular ir- regular mesh is generated that is used to extract the elevation data for rendering the map. In addition, the mesh enables the routing of edges based on the topo- graphic features of the map

    Engineering the Fast-Multipole-Multilevel Method for multicore and SIMD architectures

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    In this thesis, we present a new variant of the Fast-Mulitpole-Multilevel Method, which is used to draw large graphs. Based on the original approach by Stefan Hachul, a new algo- rithm is presented, which is optimized primarily for practical speed. In order to achieve this, special processor instructions are used to accelerate computations with complex num- bers. In addition, parts of the algorithm are executed in parallel to benefit from the widely spread multicore architectures. Besides these two rather technical improvements, we de- scribe a new construction method for a spatial space decomposition data structure, called the quadtree. The algorithm exploits the binary representation of the coordinates and shifts most of the work to the sorting of the input. Furthermore, we introduce another problem from computational geometry, the well-separated pair decomposition, and success- fully apply it in order to simplify parts of the algorithm. The resulting algorithm is able to compete in speed and layout quality even with a recently published graphics processor accelerated implementation

    Algorithms for Incremental Planar Graph Drawing and Two-page Book Embeddings

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    Subject of this work are two problems related to ordering the vertices of planar graphs. The first one is concerned with the properties of vertex-orderings that serve as a basis for incremental drawing algorithms. Such a drawing algorithm usually extends a drawing by adding the vertices step-by-step as provided by the ordering. In the field of graph drawing several orderings are in use for this purpose. Some of them, however, lack certain properties that are desirable or required for classic incremental drawing methods. We narrow down these properties, and introduce the bitonic st-ordering, an ordering which combines the features only available when using canonical orderings with the flexibility of st-orderings. The additional property of being bitonic enables an st-ordering to be used in algorithms that usually require a canonical ordering. With this in mind, we describe a linear-time algorithm that computes such an ordering for every biconnected planar graph. Unlike canonical orderings, st-orderings extend to directed graphs, in particular planar st-graphs. Being able to compute bitonic st-orderings for planar st-graphs is of particular interest for upward planar drawing algorithms, since traditional incremental algorithms for undirected planar graphs might be adapted to directed graphs. Based on this observation, we give a full characterization of the class of planar st-graphs that admit such an ordering. This includes a linear-time algorithm for recognition and ordering. Furthermore, we show that by splitting specific edges of an instance that is not part of this class, one is able to transform it into one for which then such an ordering exists. To do so, we describe a linear-time algorithm for finding the smallest set of edges to split. We show that for a planar st-graph G=(V,E), |V|−3 edge splits are sufficient and every edge is split at most once. This immediately translates to the number of bends required for upward planar poly-line drawings. More specifically, we show that every planar st-graph admits an upward planar poly-line drawing in quadratic area with at most |V|−3 bends in total and at most one bend per edge. Moreover, the drawing can be obtained in linear time. The second part is concerned with embedding planar graphs with maximum degree three and four into books. Besides providing a simplified incremental linear-time algorithm for embedding triconnected 3-planar graphs into a book of two pages, we describe a linear-time algorithm to compute a subhamiltonian cycle in a triconnected 4-planar graph

    MolMap - Visualizing Molecule Libraries as Topographic Maps

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    We present a new application for graph drawing and visualization in the context of drug discovery. Combining the scaffold-based cluster hierarchy with molecular similarity graphs — both standard concepts in cheminfor- matics — allows one to get new insights for analyzing large molecule libraries. The derived clustered graphs represent different aspects of structural similarity. We suggest visualizing them as topographic maps. Since the cluster hierarchy does not reflect the underlying graph structure as in (Gronemann and Jünger, 2012), we suggest a new partitioning algorithm that takes the edges of the graph into account. Experiments show that the new algorithm leads to significant improvements in terms of the edge lengths in the obtained drawings

    MolMap - Visualizing Molecule Libraries as Topographic Maps

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    We present a new application for graph drawing and visualization in the context of drug discovery. Combining the scaffold-based cluster hierarchy with molecular similarity graphs — both standard concepts in cheminfor- matics — allows one to get new insights for analyzing large molecule libraries. The derived clustered graphs represent different aspects of structural similarity. We suggest visualizing them as topographic maps. Since the cluster hierarchy does not reflect the underlying graph structure as in (Gronemann and Jünger, 2012), we suggest a new partitioning algorithm that takes the edges of the graph into account. Experiments show that the new algorithm leads to significant improvements in terms of the edge lengths in the obtained drawings

    Towards shortest longest edges in orthogonal graph drawing

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    Inspired by a challenge during Graph Drawing 2010 "Find an orthogonal drawing whose longest edge is as short as possible", we investigate techniques to incorporate this goal into the "standard" topology-shape-metrics approach at moderate extra computational complexity. Experiments indicate that this project is worth pursuing
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