GRIP: Graph Drawing with Intelligent Placement

Gajer, Paweł; Kobourov, Stephen G.

doi:10.7155/jgaa.00052

Cited by 83 publications

(71 citation statements)

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“…The algorithm described in this paper is used in the design of the GRIP system (Graph dRawing with Intelligent Placement) [22] which produced the drawings in Figs. 5 and 6.…”

Section: Discussionmentioning

confidence: 99%

“…This approach is similar to that used in the GEM system [5]. The local temperature heat [v] of v is simply a scaling factor of the displacement vector disp [v] of v. One particular implementation is considered in detail in [22] but regardless of the specifics of the implementation, the time complexity for updating the local temperature for each v is constant and thus the total time complexity for local temperature calculations is linear.…”

Section: Local Temperature Calculationsmentioning

confidence: 99%

“…In Section 4 we discuss possible modifications of the algorithm. Also included are several drawings obtained by the GRIP layout system [22], which is based on our algorithm.…”

Section: Introductionmentioning

confidence: 99%

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A multi-dimensional approach to force-directed layouts of large graphs

Gajer

Goodrich

Kobourov

2004

Computational Geometry

Self Cite

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We present a novel hierarchical force-directed method for drawing large graphs. The algorithm produces a graph embedding in an Euclidean space E of any dimension. A two or three dimensional drawing of the graph is then obtained by projecting a higher-dimensional embedding into a two or three dimensional subspace of E. Projecting high-dimensional drawings onto two or three dimensions often results in drawings that are "smoother" and more symmetric. Among the other notable features of our approach are the utilization of a maximal independent set filtration of the set of vertices of a graph, a fast energy function minimization strategy, efficient memory management, and an intelligent initial placement of vertices. Our implementation of the algorithm can draw graphs with tens of thousands of vertices using a negligible amount of memory in less than one minute on a mid-range PC.

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“…The algorithm described in this paper is used in the design of the GRIP system (Graph dRawing with Intelligent Placement) [22] which produced the drawings in Figs. 5 and 6.…”

Section: Discussionmentioning

confidence: 99%

Section: Local Temperature Calculationsmentioning

confidence: 99%

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A multi-dimensional approach to force-directed layouts of large graphs

Gajer

Goodrich

Kobourov

2004

Computational Geometry

Self Cite

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“…Hachul and Jünger [13] compared six large-scale graph drawing algorithms for 29 example graphs, some synthetic and some real, of which the largest had 143,437 vertices and 409,593 edges. Of the six algorithms, only three scaled well: HDE [14], FM 3 [12] and, to some extent, GRIP [8]. However, the densities of the sample graphs were small, typically less than 4.0.…”

Section: Node-link Visualization Of Large Networkmentioning

confidence: 97%

ZAME: Interactive Large-Scale Graph Visualization

Elmqvist

Goodell

et al. 2008

2008 IEEE Pacific Visualization Symposium

155

107

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INRIA Figure 1: A protein-protein interaction dataset (100,000 nodes and 1,000,000 edges) visualized using ZAME at two different levels of zoom. ABSTRACTWe present the Zoomable Adjacency Matrix Explorer (ZAME), a visualization tool for exploring graphs at a scale of millions of nodes and edges. ZAME is based on an adjacency matrix graph representation aggregated at multiple scales. It allows analysts to explore a graph at many levels, zooming and panning with interactive performance from an overview to the most detailed views. Several components work together in the ZAME tool to make this possible. Efficient matrix ordering algorithms group related elements. Individual data cases are aggregated into higher-order metarepresentations. Aggregates are arranged into a pyramid hierarchy that allows for on-demand paging to GPU shader programs to support smooth multiscale browsing. Using ZAME, we are able to explore the entire French Wikipedia-over 500,000 articles and 6,000,000 links-with interactive performance on standard consumer-level computer hardware.

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“…When no feature can be found, these approaches unfortunately are as unproductive as any forcedirected layout. Other approaches try to improve the overall quality of the layout by focusing on the initial placement of nodes [16], with no guarantee whatsoever of being able to vary the final output.…”

Section: A Related Workmentioning

confidence: 99%

One Graph, Multiple Drawings

Nadal

Melanon

2013

2013 17th International Conference on Information Visualisation

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Being able to produce a wide variety of layouts for a same graphs may prove useful when users have no preferred visual encoding for their data. The first contribution of this paper is a enhanced force-directed layout capable of producing different layouts of a same graph. We turn a well known forcedirected algorithm (GEM) into a highly parametrizable layout and control it from a genetic algorithm framework.The genetic algorithm allows to efficiently explore the parameter space of this highly parametrisable layout. The search process relies on the capability of the system to evaluate the similarity between two drawings. The second contribution of this paper is a similarity metric used as a fitness function for the genetic algorithm. Its main features are its computational cost and its insensitivity to planar homotheties.

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GRIP: Graph Drawing with Intelligent Placement

Cited by 83 publications

References 0 publications

A multi-dimensional approach to force-directed layouts of large graphs

A multi-dimensional approach to force-directed layouts of large graphs

ZAME: Interactive Large-Scale Graph Visualization

One Graph, Multiple Drawings

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