The Graph Crossing Number and Its Variants: a Survey
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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. -
No Slide Title
The ILP approach to the layered graph drawing Ago Kuusik Veskisilla Teooriapäevad 1-3.10.2004 1 Outline Introduction Hierarchical drawing & Sugiyama algorithm Linear Programming (LP) and Integer Linear Programming (ILP) Multi-level crossing minimisation ILP Maximum level planar subgraph ILP 2 Graphs Set of vertices V (real world: entities) Set of edges E ::= pairs of vertices (real world: relations) Directed graph: E ::= set of ordered pairs of vertices 3 Graph drawing Started to grow in 1960s, aim – software understanding Now, used in number of areas, for example – Software engineering (call graphs, class diagrams, database schemas) – Social studies (relationship diagrams) – Chemistry (molecular structures) 4 Graph drawing Definition: Given a graph G=(V, E), represent the graph on a plane: – Vertices – closed shapes – Edges – Jordan curves between vertex shapes (Jordan curve = a closed curve that does not intersect itself) 5 Aesthetic criteria General Application-specific – Min. number of edge – Specific vertex crossings shapes (E-R – Uniform edge diagram) direction (directed – Specific vertex graph) locations (class – Min. number of edge hierarchy) bends – Min. area 6 Hierachical drawing Given: a directed acyclic graph (A cyclic graph can be converted acyclic by reversing some edges; minimum feedback arc set is NP hard) Objective: – Uniform edge direction – Min. Number of edge crossings 7 Sugiyama algorithm Published by Sugiyama, Tagawa, Toda 1981 Vertices are placed on discrete layers Edges have uniform direction Edges connect vertices of adjacent layers Reduced edge crossings Overall balance of vertex locations 8 0. random layout 1. layering 2. sorting on layers 3. final positioning 9 1. Layering Assign vertices to discrete layers so that the edges point to common direction – Longest path layering, shortest path layering: simple DFS algorithms – Coffman-Graham layering – constrains the width of the drawing – ILP approaches (Nikolov, 2002) 10 Proper and non-proper layering Proper Non-Proper Dummy vertex 11 2. -
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. -
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. -
On Layered Drawings of Planar Graphs
On Layered Drawings of Planar Graphs Bachelor Thesis of Sarah Lutteropp At the Department of Informatics Institute of Theoretical Computer Science Reviewers: Prof. Dr. Maria Axenovich Prof. Dr. Dorothea Wagner Advisors: Dipl.-Inform. Thomas Bläsius Dr. Tamara Mchedlidze Dr. Torsten Ueckerdt Time Period: 28th January 2014 – 28th May 2014 KIT – University of the State of Baden-Wuerttemberg and National Laboratory of the Helmholtz Association www.kit.edu Acknowledgements I would like to thank my advisors Thomas Bläsius, Dr. Tamara Mchedlidze and Dr. Torsten Ueckerdt for their great support in form of many hours of discussion, useful ideas and extensive commenting on iterative versions. It was not trivial to find a topic and place for a combined mathematics and computer science thesis and I am grateful to Prof. Dr. Dorothea Wagner, who allowed me to write my thesis at her institute. I would also like to thank Prof. Dr. Dorothea Wagner and Prof. Dr. Maria Axenovich for grading my thesis. Last but not least, I would like to thank all my proofreaders (supervisors included) for giving last-minute comments on my thesis. Statement of Authorship I hereby declare that this document has been composed by myself and describes my own work, unless otherwise acknowledged in the text. Karlsruhe, 28th May 2014 iii Abstract A graph is k-level planar if it admits a planar drawing in which each vertex is mapped to one of k horizontal parallel lines and the edges are drawn as non-crossing y-monotone line segments between these lines. It is not known whether the decision problem of a graph being k-level planar is solvable in polynomial time complexity (in P) or not. -
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. -
A Generalization of the Directed Graph Layering Problem
A Generalization of the Directed Graph Layering Problem Ulf R¨uegg1, Thorsten Ehlers1, Miro Sp¨onemann2, and Reinhard von Hanxleden1 1 Dept. of Computer Science, Kiel University, Kiel, Germany furu,the,[email protected] 2 TypeFox GmbH, Kiel, Germany [email protected] Abstract. The Directed Layering Problem (DLP) solves a step of the widely used layer-based approach to automatically draw directed acyclic graphs. To cater for cyclic graphs, usually a preprocessing step is used that solves the Feedback Arc Set Problem (FASP) to make the graph acyclic before a layering is determined. Here we present the Generalized Layering Problem (GLP), which solves the combination of DLP and FASP simultaneously, allowing general graphs as input. We present an integer programming model and a heuris- tic to solve the NP-complete GLP and perform thorough evaluations on different sets of graphs and with different implementations for the steps of the layer-based approach. We observe that GLP reduces the number of dummy nodes significantly, can produce more compact drawings, and improves on graphs where DLP yields poor aspect ratios. Keywords: layer-based layout, layer assignment, linear arrangement, feedback arc set, integer programming 1 Introduction The layer-based approach is a well-established and widely used method to au- tomatically draw directed graphs. It is based on the idea to assign nodes to subsequent layers that show the inherent direction of the graph, see Fig. 1a for an example. The approach was introduced by Sugiyama et al. [19] and remains arXiv:1608.07809v1 [cs.OH] 28 Aug 2016 a subject of ongoing research.