/*
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.
Gephi is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.
Gephi is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with Gephi. If not, see <http://www.gnu.org/licenses/>.
*/
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);
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;
}
}