Algorithms for Overloaded Orthogonal Drawings
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Algorithms for Graph Visualization Flow Methods: Orthogonal Layout
Algorithms for Graph Visualization Flow Methods: Orthogonal Layout INSTITUT FUR¨ THEORETISCHE INFORMATIK · FAKULTAT¨ FUR¨ INFORMATIK Tamara Mchedlidze 18.01.2018 1 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen Orthogonal Layout • Edges consist of vertical and horizontal segments • Applied in many areas ER diagram in OGDF UML diagram by Oracle Organigram of HS Limburg Circuit diagram by Jeff Atwood 2 - 1 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen Orthogonal Layout • Edges consist of vertical and horizontal segments • Applied in many areas Aesthetic functions? ER diagram in OGDF UML diagram by Oracle Organigram of HS Limburg Circuit diagram by Jeff Atwood 2 - 2 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen Orthogonal Layout • Edges consist of vertical and horizontal segments • Applied in many areas Aesthetic functions: • number of bends • length of edges • ER diagram in OGDF width, height, area • monotonicity of edges UML diagram by Oracle • ... Organigram of HS Limburg Circuit diagram by Jeff Atwood 2 - 3 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen (Planar) Orthogonal Drawings Three-step approach: Topology { Shape { Metrics [Tamassia SIAM J. Comput. 1987] V = fv1; v2; v3; v4g E = fv1v2; v1v3; v1v4; v2v3; v2v4g 3 - 1 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen (Planar) Orthogonal Drawings Three-step approach: Topology { Shape { Metrics [Tamassia SIAM J. Comput. 1987] V = fv1; v2; v3; v4g E = fv1v2; v1v3; v1v4; v2v3; v2v4g combinatorial embedding/ planarization 4 3 Reduce Crossings 2 1 3 - 2 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen (Planar) Orthogonal Drawings Three-step approach: Topology { Shape { Metrics [Tamassia SIAM J. -
Graph Drawing Dagstuhl Seminar
05191 Abstracts Collection Graph Drawing Dagstuhl Seminar Michael Jünger1, Stephen Kobourov2 and Petra Mutzel3 1 Univ. of Köln, DE 2 Univ. of Arizona, US [email protected] 3 Univ. of Dortmund, DE [email protected] Abstract. From 08.05. to 13.05.05, the Dagstuhl Seminar 05191 Graph Drawing was held in the International Conference and Research Cen- ter (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The rst section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available. Keywords. Graph Drawing, Visualization, Layout Algorithms, Inter- active Visualization 05191 Executive Summary Graph Drawing This paper summarizes the topics, aims, and achievements of the Dagstuhl Sem- inar 05191 on Graph Drawing. Keywords: Graph drawing Joint work of: Jünger, Michael; Kobourov, Stephen; Mutzel, Petra Full Paper: http://drops.dagstuhl.de/opus/volltexte/2006/342 05191 Open Problem Session Report This is a report on an informal session intended to stimulate communication and sharing of problems. Hence the attributions and citations may contain inaccu- racies, and are certainly not complete. Keywords: Open problems, graph drawing Joint work of: Whitesides, Sue Full Paper: http://drops.dagstuhl.de/opus/volltexte/2006/338 Dagstuhl Seminar Proceedings 05191 Graph Drawing http://drops.dagstuhl.de/opus/volltexte/2006/348 2 M. Jünger, S. Kobourov and P. Mutzel Matrix Zoom: A Visual Interface to Semi-external Graphs James Abello (Rutgers Univ. -
The Open Graph Drawing Framework (OGDF)
17 The Open Graph Drawing Framework (OGDF) Markus Chimani Friedrich-Schiller-Universit¨at Jena 17.1 Introduction::::::::::::::::::::::::::::::::::::::::::::::::: 543 • Carsten Gutwenger The History of the OGDF Outline TU Dortmund 17.2 Major Design Concepts:::::::::::::::::::::::::::::::::::: 544 Modularization • Self-Contained and Portable Source Code Michael J¨unger 17.3 General Algorithms and Data Structures ::::::::::::::: 546 • University of Cologne Augmentation and Subgraph Algorithms Graph Decomposition • Planarity and Planarization Gunnar W. Klau 17.4 Graph Drawing Algorithms ::::::::::::::::::::::::::::::: 550 • Centrum Wiskunde & Planar Drawing Algorithms Hierarchical Drawing • • Informatica Algorithms Energy-Based Drawing Algorithms Drawing Clustered Graphs Karsten Klein 17.5 Success Stories :::::::::::::::::::::::::::::::::::::::::::::: 562 • • TU Dortmund SPQR-Trees Exact Crossing Minimization Upward Graph Drawing Petra Mutzel Acknowledgments :::::::::::::::::::::::::::::::::::::::::::::::::: 564 TU Dortmund References :::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 565 17.1 Introduction We present the Open Graph Drawing Framework (OGDF), a C++ library of algorithms and data structures for graph drawing. The ultimate goal of the OGDF is to help bridge the gap between theory and practice in the field of automatic graph drawing. The library offers a wide variety of algorithms and data structures, some of them requiring complex and involved implementations, e.g., algorithms for planarity testing and planarization, or data structures for graph decomposition. A substantial part of these algorithms and data structures are building blocks of graph drawing algorithms, and the OGDF aims at pro- viding such functionality in a reusable form, thus also providing a powerful platform for implementing new algorithms. The OGDF can be obtained from its website at: http://www.ogdf.net This website also provides further information like tutorials, examples, contact information, and links to related projects. -
The Graph Crossing Number and Its Variants: a Survey
The Graph Crossing Number and its Variants: A Survey Marcus Schaefer School of Computing DePaul University Chicago, Illinois 60604, USA [email protected] Submitted: Dec 20, 2011; Accepted: Apr 4, 2013; Published: April 17, 2013 Third edition, Dec 22, 2017 Mathematics Subject Classifications: 05C62, 68R10 Abstract The crossing number is a popular tool in graph drawing and visualization, but there is not really just one crossing number; there is a large family of crossing number notions of which the crossing number is the best known. We survey the rich variety of crossing number variants that have been introduced in the literature for purposes that range from studying the theoretical underpinnings of the crossing number to crossing minimization for visualization problems. 1 So, Which Crossing Number is it? The crossing number, cr(G), of a graph G is the smallest number of crossings required in any drawing of G. Or is it? According to a popular introductory textbook on combi- natorics [460, page 40] the crossing number of a graph is “the minimum number of pairs of crossing edges in a depiction of G”. So, which one is it? Is there even a difference? To start with the second question, the easy answer is: yes, obviously there is a differ- ence, the difference between counting all crossings and counting pairs of edges that cross. But maybe these different ways of counting don’t make a difference and always come out the same? That is a harder question to answer. Pach and Tóth in their paper “Which Crossing Number is it Anyway?” [369] coined the term pair crossing number, pcr, for the crossing number in the second definition. -
A New Approximation Algorithm for Bend Minimization in the Kandinsky Model
A New Approximation Algorithm for Bend Minimization in the Kandinsky Model Wilhelm Barth1, Petra Mutzel2, and Canan Yıldız1 1 Institute of Computer Graphics and Algorithms, Vienna University of Technology Favoritenstraße 9-11, 1040 Wien, Austria {barth,yildizca}@ads.tuwien.ac.at http://www.ads.tuwien.ac.at/ 2 Department of Computer Science, University of Dortmund Otto-Hahn-Str. 14, D-44227 Dortmund, Germany [email protected] http://ls11-www.cs.uni-dortmund.de/ Abstract. The Kandinsky model has been introduced by F¨oßmeier and Kaufmann in order to deal with planar orthogonal drawings of planar graphs with maximal vertex degree higher than four [7]. No polynomial- time algorithm is known for computing a (region preserving) bend mini- mal Kandinsky drawing. In this paper we suggest a new 2-approximation algorithm for this problem. Our extensive computational experiments [13] show that the quality of the computed solutions is better than those of its predecessors [6]. E.g., for all instances in the Rome graph bench- mark library [4] it computed the optimal solution, and for randomly generated triangulated graphs with up to 800 vertices, the absolute error was less than 2 on average. 1 Introduction Given a planar graph G =(V,E,F) with a fixed embedding F ,weconsider the problem of finding a region-preserving planar orthogonal drawing with the minimum number of bends. For graphs with maximal degree 4 this problem can be solved in polynomial time [12] if no parallel edge segments leaving a vertex at the same side are allowed. The idea is to set up a network in which each flow corresponds to an orthogonal drawing and vice versa. -
Algorithms for Incremental Planar Graph Drawing and Two-Page Book Embeddings
Algorithms for Incremental Planar Graph Drawing and Two-page Book Embeddings Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakult¨at der Universit¨at zu Koln¨ vorgelegt von Martin Gronemann aus Unna Koln¨ 2015 Berichterstatter (Gutachter): Prof. Dr. Michael Junger¨ Prof. Dr. Markus Chimani Prof. Dr. Bettina Speckmann Tag der m¨undlichenPr¨ufung: 23. Juni 2015 Zusammenfassung Diese Arbeit besch¨aftigt sich mit zwei Problemen bei denen es um Knoten- ordnungen in planaren Graphen geht. Hierbei werden als erstes Ordnungen betrachtet, die als Grundlage fur¨ inkrementelle Zeichenalgorithmen dienen. Solche Algorithmen erweitern in der Regel eine vorhandene Zeichnung durch schrittweises Hinzufugen¨ von Knoten in der durch die Ordnung gegebene Rei- henfolge. Zu diesem Zweck kommen im Gebiet des Graphenzeichnens verschie- dene Ordnungstypen zum Einsatz. Einigen dieser Ordnungen fehlen allerdings gewunschte¨ oder sogar fur¨ einige Algorithmen notwendige Eigenschaften. Diese Eigenschaften werden genauer untersucht und dabei ein neuer Typ von Ord- nung entwickelt, die sogenannte bitonische st-Ordnung, eine Ordnung, welche Eigenschaften kanonischer Ordnungen mit der Flexibilit¨at herk¨ommlicher st- Ordnungen kombiniert. Die zus¨atzliche Eigenschaft bitonisch zu sein erm¨oglicht es, eine st-Ordnung wie eine kanonische Ordnung zu verwenden. Es wird gezeigt, dass fur¨ jeden zwei-zusammenh¨angenden planaren Graphen eine bitonische st-Ordnung in linearer Zeit berechnet werden kann. Im Ge- gensatz zu kanonischen Ordnungen, k¨onnen st-Ordnungen naturgem¨aß auch fur¨ gerichtete Graphen verwendet werden. Diese F¨ahigkeit ist fur¨ das Zeichnen von aufw¨artsplanaren Graphen von besonderem Interesse, da eine bitonische st-Ordnung unter Umst¨anden es erlauben wurde,¨ vorhandene ungerichtete Zei- chenverfahren fur¨ den gerichteten Fall anzupassen. -
New Approaches on Octilinear Graph Drawing
New Approaches on Octilinear Graph Drawing Dissertation der Mathematisch-Naturwissenschaftlichen Fakult¨at der Eberhard Karls Universit¨atT¨ubingen zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) vorgelegt von Dipl.-Inform. (Bioinf.) Robert Krug aus Ulm T¨ubingen 2015 abc Gedruckt mit Genehmigung der Mathematisch-Naturwissenschaftlichen Fakult¨at der Eberhard Karls Universit¨atT¨ubingen. Tag der m¨undlichen Qualifikation 28.04.2015 Dekan: Prof. Dr. Wolfgang Rosenstiel 1. Berichterstatter: Prof. Dr. Michael Kaufmann 2. Berichterstatter: Prof. Dr. Peter Hauck Acknowledgements First and foremost I thank my advisor Prof. Dr. Michael Kaufmann, for giving me the opportunity to be part of his great group and write this thesis, for supporting me this whole time and enabling me to visit several international workshops and conferences. I am deeply grateful to my colleague Dr. Michael Bekos who not only par- ticipated in every research project that made it into this thesis but also gave me great support during the writing of this thesis and was a very pleasant officemate. My thanks also go to my current and former colleagues Till Bruckdorfer, Philip Effinger, Andreas Gerasch, Niklas Heinsohn, Markus Geyer, Stephan Kottler, Martin Siebenhaller and Christian Zielke who provided a very nice working atmosphere and valuable input in many scientific and non-scientific discussions during our coffee-breaks. I thank all my coauthors, namely Michael Bekos, Markus Geyer, Martin Gronemann, Michael Kaufmann, Thorsten Ludwig, Stefan N¨aherand Vin- cenzo Roselli for the pleasant and productive collaborations. I am most thankful to my friends Chrissi and Klaus who, together with Ju- lian and Laura, always offered me delicious meals and delightful company which I especially appreciated in stressful times of approaching deadlines. -
Part I: Graph Drawing – an Introduction
Part I: Graph Drawing { An Introduction Alexander Wolff Lehrstuhl fur¨ Informatik I Universit¨at Wurzburg¨ Alexander Wolff · Lehrstuhl fur¨ Informatik I · Universit¨at Wurzburg¨ Part I: Graph Drawing { An Introduction Alexander Wolff Lehrstuhl fur¨ Informatik I Universit¨at Wurzburg¨ Alexander Wolff · Lehrstuhl fur¨ Informatik I · Universit¨at Wurzburg¨ Part I: Graph Drawing { An Introduction Alexander Wolff Lehrstuhl fur¨ Informatik I Universit¨at Wurzburg¨ BandyopadhyayChakrabortyGovindarajanKrishn enduMukhopadhyayaMukhopadhyayVenkateshx Alexander Wolff · Lehrstuhl fur¨ Informatik I · Universit¨at Wurzburg¨ Part I: Graph Drawing { An Introduction Alexander Wolff Lehrstuhl fur¨ Informatik I Universit¨at Wurzburg¨ BandyopadhyayChakrabortyGovindarajanKrishn enduMukhopadhyayaMukhopadhyayVenkateshx WurzburgG¨ ¨ottingenSch¨obelKarlsruheSaarbruck¨ enGoerikHoeferKaiserslauternFrankfurtM¨ohring Alexander Wolff · Lehrstuhl fur¨ Informatik I · Universit¨at Wurzburg¨ Part I: Graph Drawing { An Introduction Alexander Wolff Lehrstuhl fur¨ Informatik I Universit¨at Wurzburg¨ BandyopadhyayChakrabortyGovindarajanKrishn enduMukhopadhyayaMukhopadhyayVenkateshx WurzburgG¨ ¨ottingenSch¨obelKarlsruheSaarbruck¨ enGoerikHoeferKaiserslauternFrankfurtM¨ohring Alexander Wolff · Lehrstuhl fur¨ Informatik I · Universit¨at Wurzburg¨ Wurzburg???¨ pronounce: [Vurtsburk]¨ Alexander Wolff · Lehrstuhl fur¨ Informatik I · Universit¨at Wurzburg¨ Wurzburg???¨ pronounce: [Vurtsburk]¨ . baroque architecture! Alexander Wolff · Lehrstuhl fur¨ Informatik I · Universit¨at Wurzburg¨ Wurzburg???¨ -
Automatic Graph Drawing with Clusters
DEGREE PROJECT IN COMPUTER SCIENCE 120 CREDITS, SECOND CYCLE STOCKHOLM, SWEDEN 2015 CluStic - Automatic graph drawing with clusters VILLIAM ASPEGREN KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF COMPUTER SCIENCE AND COMMUNICATION Master of Science Thesis CSC CluStic – Automatic graph drawing with clusters CluStic – Automatisk grafritning med avseende på kluster Villiam Aspegren Approved Examiner Supervisor 2015-12-12 Johan Håstad Michael Minock Commissioner Contact person Decerno Sven Norman Master of Science Thesis CSC KTH Computer Science SE-100 44 STOCKHOLM Abstract Finding a visually pleasing layout from a set of vertices and edges is the goal of automatic graph drawing. A requirement that has been barely explored however, is that users would like to specify portions of their layouts that are not altered by such algorithms. For example the user may have put a lot of manual effort into fixing a portion of a large layout and, while they would like an automatic layout applied to most of the layout, they do not want their work undone on the portion they manually fixed earlier. CluStic, the system developed and evaluated in this thesis, provides this capability. CluStic maintain the internal structure of a cluster by giving it priority over other elements in the graph. After high priority element has been positioned, non-priority vertices may be placed at the most appropriate remaining positions. Furthermore CluStic produces layouts which also maintain common aesthetic criteria: edge crossing minimization, layout height and edge straightening. Our method in this thesis is to first conduct an initial exploration study where we cross compare four industrial tools: Cytogate, GraphDraw, Diagram.Net and GraphNet. -
Accelerated Bend Minimization Sabine Cornelsen Andreas Karrenbauer
Journal of Graph Algorithms and Applications http://jgaa.info/ vol. 16, no. 3, pp. 635{650 (2012) DOI: 10.7155/jgaa.00265 Accelerated Bend Minimization Sabine Cornelsen Andreas Karrenbauer Department of Computer & Information Science, University of Konstanz, Germany Abstract We present an (n3=2) algorithm for minimizing the number of bends O in an orthogonal drawing of a plane graph. It has been posed as a long standing open problem at Graph Drawing 2003, whether the bound of (n7=4plog n) shown by Garg and Tamassia in 1996 could be improved. O To answer this question, we show how to solve the uncapacitated min-cost flow problem on a planar bidirected graph with bounded costs and face sizes in (n3=2) time. O Submitted: Reviewed: Revised: Accepted: Final: October 2011 February 2012 March 2012 April 2012 April 2012 Published: September 2012 Article type: Communicated by: Regular paper M. van Kreveld and B. Speckmann Andreas Karrenbauer is supported by the Zukunftskolleg of the University of Konstanz. E-mail addresses: [email protected] (Sabine Cornelsen) Andreas.Karrenbauer@ uni-konstanz.de (Andreas Karrenbauer) 636 S. Cornelsen and A. Karrenbauer Accelerated Bend Minimization 1 Introduction A drawing of a planar graph is called orthogonal if all edges are non-crossing axis-parallel polylines, i.e. sequences of finitely many horizontal and vertical line segments. The intersection point of a vertical and a horizontal line segment of an edge is a bend. Examples of orthogonal drawings can be found in Fig. 1. (a) GD Contest 2008 [13] (b) Octahedron Figure 1: Orthogonal drawings. -
55 GRAPH DRAWING Emilio Di Giacomo, Giuseppe Liotta, Roberto Tamassia
55 GRAPH DRAWING Emilio Di Giacomo, Giuseppe Liotta, Roberto Tamassia INTRODUCTION Graph drawing addresses the problem of constructing geometric representations of graphs, and has important applications to key computer technologies such as soft- ware engineering, database systems, visual interfaces, and computer-aided design. Research on graph drawing has been conducted within several diverse areas, includ- ing discrete mathematics (topological graph theory, geometric graph theory, order theory), algorithmics (graph algorithms, data structures, computational geometry, vlsi), and human-computer interaction (visual languages, graphical user interfaces, information visualization). This chapter overviews aspects of graph drawing that are especially relevant to computational geometry. Basic definitions on drawings and their properties are given in Section 55.1. Bounds on geometric and topological properties of drawings (e.g., area and crossings) are presented in Section 55.2. Sec- tion 55.3 deals with the time complexity of fundamental graph drawing problems. An example of a drawing algorithm is given in Section 55.4. Techniques for drawing general graphs are surveyed in Section 55.5. 55.1 DRAWINGS AND THEIR PROPERTIES TYPES OF GRAPHS First, we define some terminology on graphs pertinent to graph drawing. Through- out this chapter let n and m be the number of graph vertices and edges respectively, and d the maximum vertex degree (i.e., number of edges incident to a vertex). GLOSSARY Degree-k graph: Graph with maximum degree d k. ≤ Digraph: Directed graph, i.e., graph with directed edges. Acyclic digraph: Digraph without directed cycles. Transitive edge: Edge (u, v) of a digraph is transitive if there is a directed path from u to v not containing edge (u, v). -
DA14 Abstracts 27
DA14 Abstracts 27 IP1 [email protected] Shape, Homology, Persistence, and Stability CP0 My personal journey to the fascinating world of geomet- Distributed Computation of Persistent Homology ric forms started 30 years ago with the invention of al- pha shapes in the plane. It took about 10 years before Advances in algorithms for computing persistent homol- we generalized the concept to higher dimensions, we pro- ogy have reduced the computation time drastically – as duced working software with a graphics interface for the long as the algorithm does not exhaust the available mem- 3-dimensional case, and we added homology to the com- ory. Following up on a recently presented parallel method putations. Needless to say that this foreshadowed the in- for persistence computation on shared memory systems, we ception of persistent homology, because it suggested the demonstrate that a simple adaption of the standard reduc- study of filtrations to capture the scale of a shape or data tion algorithm leads to a variant for distributed systems. set. Importantly, this method has fast algorithms. The Our algorithmic design ensures that the data is distributed arguably most useful result on persistent homology is the over the nodes without redundancy; this permits the com- stability of its diagrams under perturbations. putation of much larger instances than on a single machine. The parallelism often speeds up the computation compared Herbert Edelsbrunner to sequential and even parallel shared memory algorithms. Institute of Science and Technology Austria In our experiments, we were able to compute the persis- [email protected] tent homology of filtrations with more than a billion (109) elements within seconds on a cluster with 32 nodes using less than 10GB of memory per node.