The Open Graph Drawing Framework (OGDF)
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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. -
Lipics-Socg-2017-9.Pdf (0.9
A Universal Slope Set for 1-Bend Planar Drawings Patrizio Angelini1, Michael A. Bekos2, Giuseppe Liotta3, and Fabrizio Montecchiani4 1 Wilhelm-Schickhard-Institut für Informatik, Universität Tübingen, Tübingen, Germany [email protected] 2 Wilhelm-Schickhard-Institut für Informatik, Universität Tübingen, Tübingen, Germany [email protected] 3 Universitá degli Studi di Perugia, Perugia, Italy [email protected] 4 Universitá degli Studi di Perugia, Perugia, Italy [email protected] Abstract We describe a set of ∆−1 slopes that are universal for 1-bend planar drawings of planar graphs of maximum degree ∆ ≥ 4; this establishes a new upper bound of ∆ − 1 on the 1-bend planar slope number. By universal we mean that every planar graph of degree ∆ has a planar drawing with at most one bend per edge and such that the slopes of the segments forming the edges belong to the given set of slopes. This improves over previous results in two ways: Firstly, the best previously 3 known upper bound for the 1-bend planar slope number was 2 (∆ − 1) (the known lower bound 3 being 4 (∆ − 1)); secondly, all the known algorithms to construct 1-bend planar drawings with O(∆) slopes use a different set of slopes for each graph and can have bad angular resolution, while our algorithm uses a universal set of slopes, which also guarantees that the minimum angle π between any two edges incident to a vertex is (∆−1) . 1998 ACM Subject Classification G.2.1 Combinatorics, G.2.2 Graph Theory Keywords and phrases Slope number, 1-bend drawings, planar graphs, angular resolution Digital Object Identifier 10.4230/LIPIcs.SoCG.2017.9 1 Introduction This paper is concerned with planar drawings of graphs such that each edge is a poly-line with few bends, each segment has one of a limited set of possible slopes, and the drawing has good angular resolution, i.e. -
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. -
An Effective Crossing Minimisation Heuristic Based on Star Insertion
Journal of Graph Algorithms and Applications http://jgaa.info/ vol. 0, no. 0, pp. 0–0 (0) DOI: An effective crossing minimisation heuristic based on star insertion Kieran Clancy 1 Michael Haythorpe 1,2 Alex Newcombe 1 1College of Science and Engineering, Flinders University, 1284 South Road, Tonsley, Australia 2Corresponding author Abstract We present a new heuristic method for minimising crossings in a graph. The method is based upon repeatedly solving the so-called star insertion problem in the setting where the combinatorial embedding is fixed, and has several desirable characteristics for practical use. We introduce the method, discuss some aspects of algorithm design for our implementation, and provide some experimental results. The results indicate that our method compares well to existing methods, and also that it is suitable for dense instances. Submitted: Reviewed: Revised: Accepted: Final: May 2018 November 2018 January 2019 February 2019 February 2019 Published: ??? arXiv:1804.09900v3 [math.CO] 15 Feb 2019 Article type: Communicated by: Regular paper G. Liotta E-mail addresses: kieran.clancy@flinders.edu.au (Kieran Clancy) michael.haythorpe@flinders.edu.au (Michael Haythorpe) alex.newcombe@flinders.edu.au (Alex Newcombe) JGAA,0(0)0–0(0) 1 1 Introduction The crossing number of a graph G, denoted by cr(G), is defined as the mini- mum number of pairwise edge intersections of any drawing of G in the plane. Crossing numbers have been the source of many challenging problems since their introduction by Tur´an in the 1950s [33]. Determining the crossing number of a graph is NP-hard [21] and remains NP-hard even for restricted versions of the problem, such as finding cr(G) for a planar graph with the addition of a single edge [6]. -
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. -
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). -
Technical Foundations
Technical Foundations Michael J¨unger1 and Petra Mutzel2 1 University of Cologne, Department of Computer Science, Pohligstraße 1, D-50969 K¨oln, Germany 2 Vienna University of Technology, Institute of Computer Graphics and Algorithms, Favoritenstraße 9–11, A-1040 Wien, Austria 1 Introduction Graph drawing software relies on a variety of mathematical results, mainly in graph theory, topology,andgeometry, as well as computer science techniques, mainly in the areas algorithms and data structures, software engineering, and user interfaces. Many of the core techniques used in automatic graph drawing come from the intersection of mathematics and computer science in combinatorial and continuous optimization. Even though automatic graph drawing is a relatively young scientific field, a few generic approaches have emerged in the graph drawing community. They allow a classification of layout methods so that most software packages implement variations of such approaches. The purpose of this chapter is to lay the foundations for all subsequent chapters so that they can be read independently from each other while re- ferring back to the common material presented here. This chapter has been written based on the requirements and the contributions of all authors in this book. This chapter is not an introduction to automatic graph drawing, because it is neither complete nor balanced. In order to avoid repetitions, we only explain subjects that are basic or used in at least two subsequent chapters. The following chapters contain a lot of additional material. For introductions into the field of automatic graph drawing we recommend the books “Graph Drawing” by Di Battista, Eades, Tamassia, and Tollis [23] and “Drawing Graphs” edited by Kaufmann and Wagner [52].