List of usage examples for javax.swing JApplet subclass-usage
From source file UNUSED.JUNGsamples.TreeLayoutDemo.java
/** * Demonsrates TreeLayout and RadialTreeLayout. * @author Tom Nelson * */ @SuppressWarnings("serial")
From source file edu.uci.ics.jung.samples.TreeLayoutDemo.java
/** * Demonsrates TreeLayout and RadialTreeLayout. * @author Tom Nelson * */ @SuppressWarnings("serial")
From source file io.datalayer.jung.ClusteringDemo.java
/**
* This simple app demonstrates how one can use our algorithms and visualization libraries in unison.
* In this case, we generate use the Zachary karate club data set, widely known in the social networks literature, then
* we cluster the vertices using an edge-betweenness clusterer, and finally we visualize the graph using
* Fruchtermain-Rheingold layout and provide a slider so that the user can adjust the clustering granularity.
* @author Scott White
From source file UNUSED.JUNGsamples.ClusteringDemo.java
/**
* This simple app demonstrates how one can use our algorithms and visualization libraries in unison.
* In this case, we generate use the Zachary karate club data set, widely known in the social networks literature, then
* we cluster the vertices using an edge-betweenness clusterer, and finally we visualize the graph using
* Fruchtermain-Rheingold layout and provide a slider so that the user can adjust the clustering granularity.
* @author Scott White
From source file edu.uci.ics.jung.samples.ClusteringDemo.java
/**
* This simple app demonstrates how one can use our algorithms and visualization libraries in unison.
* In this case, we generate use the Zachary karate club data set, widely known in the social networks literature, then
* we cluster the vertices using an edge-betweenness clusterer, and finally we visualize the graph using
* Fruchtermain-Rheingold layout and provide a slider so that the user can adjust the clustering granularity.
* @author Scott White
From source file test.visualization.ClusteringDemo.java
/**
* This simple app demonstrates how one can use our algorithms and visualization libraries in unison.
* In this case, we generate use the Zachary karate club data set, widely known in the social networks literature, then
* we cluster the vertices using an edge-betweenness clusterer, and finally we visualize the graph using
* Fruchtermain-Rheingold layout and provide a slider so that the user can adjust the clustering granularity.
* @author Scott White
From source file com.google.code.facebook.graph.sna.applet.TreeLayoutDemo.java
/** * Demonsrates TreeLayout and RadialTreeLayout. * @author Tom Nelson * */ @SuppressWarnings("serial")
From source file cimat.tesis.sna.visualization.ClusteringDemo.java
/**
* This simple app demonstrates how one can use our algorithms and visualization libraries in unison.
* In this case, we generate use the Zachary karate club data set, widely known in the social networks literature, then
* we cluster the vertices using an edge-betweenness clusterer, and finally we visualize the graph using
* Fruchtermain-Rheingold layout and provide a slider so that the user can adjust the clustering granularity.
* @author Scott White
From source file by.bsuir.main.Graph.java
/** * Demonsrates TreeLayout and RadialTreeLayout. * @author Tom Nelson * */ @SuppressWarnings("serial")
From source file com.google.code.facebook.graph.sna.applet.ClusteringDemo.java
/**
* This simple app demonstrates how one can use our algorithms and visualization libraries in unison.
* In this case, we generate use the Zachary karate club data set, widely known in the social networks literature, then
* we cluster the vertices using an edge-betweenness clusterer, and finally we visualize the graph using
* Fruchtermain-Rheingold layout and provide a slider so that the user can adjust the clustering granularity.
* @author Scott White