/*
Copyright 2008-2011 Gephi
Authors : Patick J. McSweeney <pjmcswee@syr.edu>, Sebastien Heymann <seb@gephi.org>
Website : http://www.gephi.org
This file is part of Gephi.
DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS HEADER.
Copyright 2011 Gephi Consortium. All rights reserved.
The contents of this file are subject to the terms of either the GNU
General Public License Version 3 only ("GPL") or the Common
Development and Distribution License("CDDL") (collectively, the
"License"). You may not use this file except in compliance with the
License. You can obtain a copy of the License at
http://gephi.org/about/legal/license-notice/
or /cddl-1.0.txt and /gpl-3.0.txt. See the License for the
specific language governing permissions and limitations under the
License. When distributing the software, include this License Header
Notice in each file and include the License files at
/cddl-1.0.txt and /gpl-3.0.txt. If applicable, add the following below the
License Header, with the fields enclosed by brackets [] replaced by
your own identifying information:
"Portions Copyrighted [year] [name of copyright owner]"
If you wish your version of this file to be governed by only the CDDL
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"[Contributor] elects to include this software in this distribution
under the [CDDL or GPL Version 3] license." If you do not indicate a
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However, if you add GPL Version 3 code and therefore, elected the GPL
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Contributor(s):
Portions Copyrighted 2011 Gephi Consortium.
*/
package org.gephi.statistics.plugin;
import java.io.IOException;
import java.util.HashMap;
import org.gephi.statistics.spi.Statistics;
import org.gephi.graph.api.*;
import java.util.LinkedList;
import java.util.ListIterator;
import java.util.Map;
import java.util.Stack;
import org.gephi.data.attributes.api.AttributeTable;
import org.gephi.data.attributes.api.AttributeColumn;
import org.gephi.data.attributes.api.AttributeModel;
import org.gephi.data.attributes.api.AttributeOrigin;
import org.gephi.data.attributes.api.AttributeRow;
import org.gephi.data.attributes.api.AttributeType;
import org.gephi.utils.TempDirUtils;
import org.gephi.utils.TempDirUtils.TempDir;
import org.gephi.utils.longtask.spi.LongTask;
import org.gephi.utils.progress.Progress;
import org.gephi.utils.progress.ProgressTicket;
import org.jfree.chart.ChartFactory;
import org.jfree.chart.JFreeChart;
import org.jfree.chart.plot.PlotOrientation;
import org.jfree.data.xy.XYSeries;
import org.jfree.data.xy.XYSeriesCollection;
import org.openide.util.Exceptions;
import org.openide.util.Lookup;
/**
* Ref: Ulrik Brandes, A Faster Algorithm for Betweenness Centrality,
* in Journal of Mathematical Sociology 25(2):163-177, (2001)
*
* @author pjmcswee
*/
public class GraphDistance implements Statistics, LongTask {
public static final String BETWEENNESS = "betweenesscentrality";
public static final String CLOSENESS = "closnesscentrality";
public static final String ECCENTRICITY = "eccentricity";
/** */
private double[] betweenness;
/** */
private double[] closeness;
/** */
private double[] eccentricity;
/** */
private int diameter;
private int radius;
/** */
private double avgDist;
/** */
private int N;
/** */
private boolean isDirected;
/** */
private ProgressTicket progress;
/** */
private boolean isCanceled;
private int shortestPaths;
private boolean isNormalized;
public GraphDistance() {
GraphController graphController = Lookup.getDefault().lookup(GraphController.class);
if (graphController != null && graphController.getModel() != null) {
isDirected = graphController.getModel().isDirected();
}
}
public double getPathLength() {
return avgDist;
}
/**
*
* @return
*/
public double getDiameter() {
return diameter;
}
/**
*
* @param graphModel
*/
public void execute(GraphModel graphModel, AttributeModel attributeModel) {
HierarchicalGraph graph = null;
if (isDirected) {
graph = graphModel.getHierarchicalDirectedGraphVisible();
} else {
graph = graphModel.getHierarchicalUndirectedGraphVisible();
}
execute(graph, attributeModel);
}
public void execute(HierarchicalGraph hgraph, AttributeModel attributeModel) {
isCanceled = false;
AttributeTable nodeTable = attributeModel.getNodeTable();
AttributeColumn eccentricityCol = nodeTable.getColumn(ECCENTRICITY);
AttributeColumn closenessCol = nodeTable.getColumn(CLOSENESS);
AttributeColumn betweenessCol = nodeTable.getColumn(BETWEENNESS);
if (eccentricityCol == null) {
eccentricityCol = nodeTable.addColumn(ECCENTRICITY, "Eccentricity", AttributeType.DOUBLE, AttributeOrigin.COMPUTED, new Double(0));
}
if (closenessCol == null) {
closenessCol = nodeTable.addColumn(CLOSENESS, "Closeness Centrality", AttributeType.DOUBLE, AttributeOrigin.COMPUTED, new Double(0));
}
if (betweenessCol == null) {
betweenessCol = nodeTable.addColumn(BETWEENNESS, "Betweenness Centrality", AttributeType.DOUBLE, AttributeOrigin.COMPUTED, new Double(0));
}
hgraph.readLock();
N = hgraph.getNodeCount();
betweenness = new double[N];
eccentricity = new double[N];
closeness = new double[N];
diameter = 0;
avgDist = 0;
shortestPaths = 0;
radius = Integer.MAX_VALUE;
HashMap<Node, Integer> indicies = new HashMap<Node, Integer>();
int index = 0;
for (Node s : hgraph.getNodes()) {
indicies.put(s, index);
index++;
}
Progress.start(progress, hgraph.getNodeCount());
int count = 0;
for (Node s : hgraph.getNodes()) {
Stack<Node> S = new Stack<Node>();
LinkedList<Node>[] P = new LinkedList[N];
double[] theta = new double[N];
int[] d = new int[N];
for (int j = 0; j < N; j++) {
P[j] = new LinkedList<Node>();
theta[j] = 0;
d[j] = -1;
}
int s_index = indicies.get(s);
theta[s_index] = 1;
d[s_index] = 0;
LinkedList<Node> Q = new LinkedList<Node>();
Q.addLast(s);
while (!Q.isEmpty()) {
Node v = Q.removeFirst();
S.push(v);
int v_index = indicies.get(v);
EdgeIterable edgeIter = null;
if (isDirected) {
edgeIter = ((HierarchicalDirectedGraph) hgraph).getOutEdgesAndMetaOutEdges(v);
} else {
edgeIter = hgraph.getEdgesAndMetaEdges(v);
}
for (Edge edge : edgeIter) {
Node reachable = hgraph.getOpposite(v, edge);
int r_index = indicies.get(reachable);
if (d[r_index] < 0) {
Q.addLast(reachable);
d[r_index] = d[v_index] + 1;
}
if (d[r_index] == (d[v_index] + 1)) {
theta[r_index] = theta[r_index] + theta[v_index];
P[r_index].addLast(v);
}
}
}
double reachable = 0;
for (int i = 0; i < N; i++) {
if (d[i] > 0) {
avgDist += d[i];
eccentricity[s_index] = (int) Math.max(eccentricity[s_index], d[i]);
closeness[s_index] += d[i];
diameter = Math.max(diameter, d[i]);
reachable++;
}
}
radius = (int) Math.min(eccentricity[s_index], radius);
if (reachable != 0) {
closeness[s_index] /= reachable;
}
shortestPaths += reachable;
double[] delta = new double[N];
while (!S.empty()) {
Node w = S.pop();
int w_index = indicies.get(w);
ListIterator<Node> iter1 = P[w_index].listIterator();
while (iter1.hasNext()) {
Node u = iter1.next();
int u_index = indicies.get(u);
delta[u_index] += (theta[u_index] / theta[w_index]) * (1 + delta[w_index]);
}
if (w != s) {
betweenness[w_index] += delta[w_index];
}
}
count++;
if (isCanceled) {
hgraph.readUnlockAll();
return;
}
Progress.progress(progress, count);
}
avgDist /= shortestPaths;//mN * (mN - 1.0f);
for (Node s : hgraph.getNodes()) {
AttributeRow row = (AttributeRow) s.getNodeData().getAttributes();
int s_index = indicies.get(s);
if (!isDirected) {
betweenness[s_index] /= 2;
}
if (isNormalized) {
closeness[s_index] = (closeness[s_index] == 0) ? 0 : 1.0 / closeness[s_index];
betweenness[s_index] /= isDirected ? (N - 1) * (N - 2) : (N - 1) * (N - 2) / 2;
}
row.setValue(eccentricityCol, eccentricity[s_index]);
row.setValue(closenessCol, closeness[s_index]);
row.setValue(betweenessCol, betweenness[s_index]);
}
hgraph.readUnlock();
}
public void setNormalized(boolean isNormalized) {
this.isNormalized = isNormalized;
}
public boolean isNormalized() {
return isNormalized;
}
public void setDirected(boolean isDirected) {
this.isDirected = isDirected;
}
public boolean isDirected() {
return isDirected;
}
private String createImageFile(TempDir tempDir, double[] pVals, String pName, String pX, String pY) {
//distribution of values
Map<Double, Integer> dist = new HashMap<Double, Integer>();
for (int i = 0; i < N; i++) {
Double d = pVals[i];
if (dist.containsKey(d)) {
Integer v = dist.get(d);
dist.put(d, v + 1);
} else {
dist.put(d, 1);
}
}
//Distribution series
XYSeries dSeries = ChartUtils.createXYSeries(dist, pName);
XYSeriesCollection dataset = new XYSeriesCollection();
dataset.addSeries(dSeries);
JFreeChart chart = ChartFactory.createXYLineChart(
pName,
pX,
pY,
dataset,
PlotOrientation.VERTICAL,
true,
false,
false);
chart.removeLegend();
ChartUtils.decorateChart(chart);
ChartUtils.scaleChart(chart, dSeries, isNormalized);
return ChartUtils.renderChart(chart, pName + ".png");
}
/**
*
* @return
*/
public String getReport() {
String htmlIMG1 = "";
String htmlIMG2 = "";
String htmlIMG3 = "";
try {
TempDir tempDir = TempDirUtils.createTempDir();
htmlIMG1 = createImageFile(tempDir, betweenness, "Betweenness Centrality Distribution", "Value", "Count");
htmlIMG2 = createImageFile(tempDir, closeness, "Closeness Centrality Distribution", "Value", "Count");
htmlIMG3 = createImageFile(tempDir, eccentricity, "Eccentricity Distribution", "Value", "Count");
} catch (IOException ex) {
Exceptions.printStackTrace(ex);
}
String report = "<HTML> <BODY> <h1>Graph Distance Report </h1> "
+ "<hr>"
+ "<br>"
+ "<h2> Parameters: </h2>"
+ "Network Interpretation: " + (isDirected ? "directed" : "undirected") + "<br />"
+ "<br /> <h2> Results: </h2>"
+ "Diameter: " + diameter + "<br />"
+ "Radius: " + radius + "<br />"
+ "Average Path length: " + avgDist + "<br />"
+ "Number of shortest paths: " + shortestPaths + "<br /><br />"
+ htmlIMG1 + "<br /><br />"
+ htmlIMG2 + "<br /><br />"
+ htmlIMG3
+ "<br /><br />" + "<h2> Algorithm: </h2>"
+ "Ulrik Brandes, <i>A Faster Algorithm for Betweenness Centrality</i>, in Journal of Mathematical Sociology 25(2):163-177, (2001)<br />"
+ "</BODY> </HTML>";
return report;
}
/**
*
* @return
*/
public boolean cancel() {
this.isCanceled = true;
return true;
}
/**
*
* @param progressTicket
*/
public void setProgressTicket(ProgressTicket progressTicket) {
this.progress = progressTicket;
}
}