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Walrus - Graph Visualization Tool

Walrus - Graph Visualization Tool
Source Code Available The source code to Walrus is now available under the GNU GPL. You may download the source code below. Description Walrus is a tool for interactively visualizing large directed graphs in three-dimensional space. Walrus computes its layout based on a user-supplied spanning tree. Walrus uses 3D hyperbolic geometry to display graphs under a fisheye-like distortion. Walrus is being developed by Young Hyun at CAIDA. Applicability Please note that Walrus currently has the following requirements, restrictions, or limitations which may render it unsuitable for a given problem domain or dataset: Only directed graphs are supported.Only connected graphs with reachable nodes are supported. Galleries The following galleries show graphs of various sizes and complexity. Implemented Features Features Under Consideration more options for coloring objects (such as with a perceptually uniform colorscale)filtering and other interactive processing Requirements Download Changes References Related:  Social Network Analysis

SoNIA - Social Network Image Animator Social Network Image Animator What is it? SoNIA is a Java-based package for visualizing dynamic or longitudinal "network" data. Our intention for SoNIA is to read-in dynamic network information from various formats, aid the user in constructing "meaningful" layouts, and export the resulting images or "movies" of the network, along with information about the techniques and parameter settings used to construct the layouts, and some form of statistic indicating the "accuracy" or degree of distortion present in the layout. What else is SoNIA for? In addition, we hope that SoNIA will have other uses. Another mode of use that SoNIA supports is that of a "browser" for time-based network data. Authors SoNIA is currently under development by Dan McFarland and Skye Bender-deMoll, originally supported by a Research Incentive Award provided by Stanford University's Office of Technology and Liscensing (grant # 2-CDZ-108). Other contributors include:

D veloppement avanc avec Eclipse Zest Dans l'article précédent, Introduction à ZestIntroduction à Zest, nous avons vu comment construire un graphe, que ce soit à partir d'un modèle en utilisant les mêmes mécanismes que JFace, ou directement en créant nœuds et branches. Cet article reprend l'exemple de l'article précédent, et se propose de montrer comment enrichir le graphe de diverses manières : soit par le biais de styles personnalisés, de menus contextuels, ou encore par la mise en place d'un zoom, ou de layouts différents. Ce tutoriel suppose que vous disposiez des connaissances de base sur les technologies suivantes : Par ailleurs, nous repartons sur le graphe orienté "branches" de l'article d'introduction, contenu dans la vue "LinkView". Les sources sont disponibles ici (FTP)src-intro-ftp ou ici (HTTP)src-intro-http. La boîte à outils Zest possède plusieurs algorithmes d'agencement pour un graphe, qui modifient la disposition initiale du graphe lors de sa construction. LinkGraphView.java Sélectionnez OpenRoadAction.java

SocNetV - Social Networks Visualization and Analysis Software The LibSea Graph File Format and Java Graph Library Source Code / Download The source code to LibSea is available under the GNU Lesser GPL. You may download LibSea from either libsea-0.1-src.tar.gz or libsea-0.1-src.zip. A precompiled jar file is distributed with the Walrus graph visualization tool. About the LibSea Graph File Format The LibSea file format allows you to specify the topology of directed graphs using nodes, links, and paths (paths are sequences of links)attach data to nodes, links, and paths in a flexible mannerimplement application-specific conventions and semantics Users can attach data to topological elements (nodes, links, and paths) using attributes. LibSea graph files can also contain qualifiers. For example, there is no direct method of specifying a spanning tree in a LibSea graph file, but this can be easily accomplished with a qualifier. LibSea Java Graph Library It is relatively easy to design a data structure that can compactly represent the topology of graphs, even graphs with millions of nodes. Applicability

Data Visualization Software | Tulip The Draw2d Examples - A Hidden Treasure While this is not really documented, hidden in the depths of the GEF cvs repository, there is quite a bunch of nice little Draw2d examples, which may help beginners as well as prospective experts in understanding the framework's principles and mechanisms. All that has to be done in order to access them is to check out the org.eclipse.draw2d.examples plug-in from the examples module of the repository (please follow GEF's getting involved pages for detailed instructions on how to access the repository). All examples are implemented as standalone Java applications, so they can quite easily be executed. Of course, every set of examples has to include a "Hello World". But there's more. And what about playing around a bit with shape styles... ... or learning more about the behavior of locators? There's also something to demonstrate Draw2d's more advanced features like shortest path connection routing ... ... directed graph layout ... ... zooming ... ... printing ... ... or text flows.

Complex Adaptive Systems Modeling - a SpringerOpen journal Social Network Analysis: A Systematic Approach for Investigating Social network analysis (SNA) is often confused with social networking sites, such as Facebook, when in fact, SNA is an analytical tool that can be used to map and measure social relations. Through quantitative metrics and robust visual displays, police can use SNA to discover, analyze, and visualize the social networks of criminal suspects. SNA, a social science methodology, serves as a valuable tool for law enforcement. While technologically sophisticated, SNA proves easy to employ. Using available data, police departments structure the examination of an offender’s social network in ways not previously possible. Manual examination of social networks tends to be difficult, time consuming, and arbitrary, making it more prone to error. SNA derives its value from human organization and social interaction for criminal and noncriminal purposes. Social networks that enable crime are not mutually exclusive from the networks of law- abiding citizens. Theory and Method Case Study Results Analysis

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