48,901 research outputs found
Computing NodeTrix Representations of Clustered Graphs
NodeTrix representations are a popular way to visualize clustered graphs;
they represent clusters as adjacency matrices and inter-cluster edges as curves
connecting the matrix boundaries. We study the complexity of constructing
NodeTrix representations focusing on planarity testing problems, and we show
several NP-completeness results and some polynomial-time algorithms. Building
on such algorithms we develop a JavaScript library for NodeTrix representations
aimed at reducing the crossings between edges incident to the same matrix.Comment: Appears in the Proceedings of the 24th International Symposium on
Graph Drawing and Network Visualization (GD 2016
Cupe - the CUBIC Pathway Editor
Cupe(CUBIC Pathway Editor) is a graphical editor for the automatic or interactive generation and display of metabolic networks. Cupe combines the user guidance by its graphical user interface (GUI) with the ability of automatic graph drawing and the possibility for manual interaction. Furthermore, it provides a programming interface for analysis, simulation and cross linking of reactions.
One of the outstanding features of Cupe is its automatic layout mechanism which is provided by utilising the well-known AGD library. The adaptation and development
of layout algorithms for the requirements of metabolic networks is an interdisciplinary cooperation between the Department of Computer Science, Cologne University, the
Chair of Algorithm Engineering, Dortmund University, and the Cologne University Bioinformatics Center.
Poster presentation in 14th International Symposium on Graph Drawin
Evolutionary Meta Layout of Graphs
A graph drawing library is like a toolbox, allowing experts to select and configure a specialized algorithm in order to meet the requirements of their diagram visualization application. However, without expert knowledge of the algorithms the potential of such a toolbox cannot be fully exploited. This gives rise to the question whether the process of selecting and configuring layout algorithms can be automated such that good layouts are produced. In this paper we call this kind of automation "meta layout." We propose a genetic representation that can be used in meta heuristics for meta layout and contribute new metrics for the evaluation of graph drawings. Furthermore, we examine the use of an evolutionary algorithm to search for optimal solutions and evaluate this approach both with automatic experiments and a user study. The results confirm that our methods can actually help users to find good layout configurations
An Interactive Tool to Explore and Improve the Ply Number of Drawings
Given a straight-line drawing of a graph , for every vertex
the ply disk is defined as a disk centered at where the radius of
the disk is half the length of the longest edge incident to . The ply number
of a given drawing is defined as the maximum number of overlapping disks at
some point in . Here we present a tool to explore and evaluate
the ply number for graphs with instant visual feedback for the user. We
evaluate our methods in comparison to an existing ply computation by De Luca et
al. [WALCOM'17]. We are able to reduce the computation time from seconds to
milliseconds for given drawings and thereby contribute to further research on
the ply topic by providing an efficient tool to examine graphs extensively by
user interaction as well as some automatic features to reduce the ply number.Comment: Appears in the Proceedings of the 25th International Symposium on
Graph Drawing and Network Visualization (GD 2017
Experimental analysis of the accessibility of drawings with few segments
The visual complexity of a graph drawing is defined as the number of
geometric objects needed to represent all its edges. In particular, one object
may represent multiple edges, e.g., one needs only one line segment to draw two
collinear incident edges. We study the question if drawings with few segments
have a better aesthetic appeal and help the user to asses the underlying graph.
We design an experiment that investigates two different graph types (trees and
sparse graphs), three different layout algorithms for trees, and two different
layout algorithms for sparse graphs. We asked the users to give an aesthetic
ranking on the layouts and to perform a furthest-pair or shortest-path task on
the drawings.Comment: Appears in the Proceedings of the 25th International Symposium on
Graph Drawing and Network Visualization (GD 2017
The Open Graph Archive: A Community-Driven Effort
In order to evaluate, compare, and tune graph algorithms, experiments on well
designed benchmark sets have to be performed. Together with the goal of
reproducibility of experimental results, this creates a demand for a public
archive to gather and store graph instances. Such an archive would ideally
allow annotation of instances or sets of graphs with additional information
like graph properties and references to the respective experiments and results.
Here we examine the requirements, and introduce a new community project with
the aim of producing an easily accessible library of graphs. Through successful
community involvement, it is expected that the archive will contain a
representative selection of both real-world and generated graph instances,
covering significant application areas as well as interesting classes of
graphs.Comment: 10 page
A Note on the Practicality of Maximal Planar Subgraph Algorithms
Given a graph , the NP-hard Maximum Planar Subgraph problem (MPS) asks for
a planar subgraph of with the maximum number of edges. There are several
heuristic, approximative, and exact algorithms to tackle the problem, but---to
the best of our knowledge---they have never been compared competitively in
practice. We report on an exploratory study on the relative merits of the
diverse approaches, focusing on practical runtime, solution quality, and
implementation complexity. Surprisingly, a seemingly only theoretically strong
approximation forms the building block of the strongest choice.Comment: Appears in the Proceedings of the 24th International Symposium on
Graph Drawing and Network Visualization (GD 2016
GraphCombEx: A Software Tool for Exploration of Combinatorial Optimisation Properties of Large Graphs
We present a prototype of a software tool for exploration of multiple
combinatorial optimisation problems in large real-world and synthetic complex
networks. Our tool, called GraphCombEx (an acronym of Graph Combinatorial
Explorer), provides a unified framework for scalable computation and
presentation of high-quality suboptimal solutions and bounds for a number of
widely studied combinatorial optimisation problems. Efficient representation
and applicability to large-scale graphs and complex networks are particularly
considered in its design. The problems currently supported include maximum
clique, graph colouring, maximum independent set, minimum vertex clique
covering, minimum dominating set, as well as the longest simple cycle problem.
Suboptimal solutions and intervals for optimal objective values are estimated
using scalable heuristics. The tool is designed with extensibility in mind,
with the view of further problems and both new fast and high-performance
heuristics to be added in the future. GraphCombEx has already been successfully
used as a support tool in a number of recent research studies using
combinatorial optimisation to analyse complex networks, indicating its promise
as a research software tool
JGraphT -- A Java library for graph data structures and algorithms
Mathematical software and graph-theoretical algorithmic packages to
efficiently model, analyze and query graphs are crucial in an era where
large-scale spatial, societal and economic network data are abundantly
available. One such package is JGraphT, a programming library which contains
very efficient and generic graph data-structures along with a large collection
of state-of-the-art algorithms. The library is written in Java with stability,
interoperability and performance in mind. A distinctive feature of this library
is the ability to model vertices and edges as arbitrary objects, thereby
permitting natural representations of many common networks including
transportation, social and biological networks. Besides classic graph
algorithms such as shortest-paths and spanning-tree algorithms, the library
contains numerous advanced algorithms: graph and subgraph isomorphism; matching
and flow problems; approximation algorithms for NP-hard problems such as
independent set and TSP; and several more exotic algorithms such as Berge graph
detection. Due to its versatility and generic design, JGraphT is currently used
in large-scale commercial, non-commercial and academic research projects. In
this work we describe in detail the design and underlying structure of the
library, and discuss its most important features and algorithms. A
computational study is conducted to evaluate the performance of JGraphT versus
a number of similar libraries. Experiments on a large number of graphs over a
variety of popular algorithms show that JGraphT is highly competitive with
other established libraries such as NetworkX or the BGL.Comment: Major Revisio
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