Documentation / Tutorials

Working with algorithms and generators


We see algorithms like something which can be initialized on a graph and then computed. For example, an algorithm can colorize nodes or edges of a graph ; an other can compute a spanned tree …

The org.graphstream.algorithm.Algorithm interface defines the structure of an algorithm. It contains two methods :

  • init( Graph g ), which is the initialization step of the algorithm ;
  • compute(), which launches the algorithm.

Why does we not just use a compute(Graph) method ?

The initialization step and computing step are located in different methods because you may have to make a new computation of your algorithm without calling the initialization step again. This initialization step must contain code which is unique for a graph and it has to be called again only if you want to reset data linked to the algorithm or to change the graph.

This is a good way to use algorithm:

 Graph g = ... ;

 // Creation of the graph

 Algorithm a = ... ; // My algorithm

 // Others operations on g

 a.compute(); // Update results

A basic algorithm example

The following is an example of a basic algorithm that computes min, max and average degree in the graph:

 public class DegreesAlgorithm implements Algorithm {
    Graph theGraph;
    int minDegree, maxDegree, avgDegree;
    public void init(Graph graph) {
        theGraph = graph;
    public void compute() {
        avgDegree = 0;
        minDegree = Integer.MAX_VALUE;
        maxDegree = 0;
        for(Node n : theGraph.getEachNode() ) {
            int deg = n.getDegree();
            minDegree = Math.min(minDegree, d);
            maxDegree = Math.max(maxDegree, d);
            avgDegree += d;
        avgDegree /= theGraph.getNodeCount();
    public int getMaxDegree() {
        return maxDegree;
    public int getMinDegree() {
        return minDegree;
    public int getAverageDegree() {
        return avgDegree;


On GraphStream, dynamicity is at the foreground so it is normal that algorithms can be dynamic to. The interface org.graphstream.algorithm.DynamicAlgorithm extends Algorithm and introduces a new method terminate() which defines the end of the algorithm.

Use of this kind of algorithms could be:

 Graph g = ... ;

 // Creation of the graph

 DynamicAlgorithm da = ... ;

 while( ... ) // something to do


A basic dynamic algorithm example

In this example, computation is done continuously in a loop. One may want to make the computation when receiving events. This can be done with a Sink that will trigger the computation. For example, this is a dynamic algorithm where computation is done when a node is added:

 public class ApparitionAlgorithm extends SinkAdapter implements
 		DynamicAlgorithm {
    Graph theGraph;
    HashMap<String, Integer> apparitions;
    double avg;
    public void init(Graph graph) {
        theGraph = graph;
        avg = 0;
    public void compute() {
        avg = 0;
        for (int a : apparitions.values())
            avg += a;
            avg /= apparitions.size();
    public void terminate() {
    public double getAverageApparitions() {
        return avg;
    public int getApparitions(String nodeId) {
        return apparitions.get(nodeId);
    public void nodeAdded(String sourceId, long timeId, String nodeId) {
        int a = 0;
        if (apparitions.containsKey(nodeId))
            a = apparitions.get(nodeId);
        apparitions.put(nodeId, a + 1);
    public void stepBegins(String sourceId, long timeId, double step) {

In this last example, init(..) is use to set a link between the graph and the algorithm and end() removes this link.


A generator is an algorithmic source of events that produce a graph according to criteria. Generators are composed of :

  1. a begin() method that is called one time at the beginning,
  2. a nextEvents() that produces some new events and that can be called as much as more events are available,
  3. a end() method that closes the generation.

A trivial example is a generator producing a full connected graph that adds a new node at each iteration and connects it with all previous nodes.

Generator is a Source, so transmission of events is done in the classic Source/Sink way:

 Generator gen = ...;
 Graph graph = ...;
 for(int i = 0; i < 100; i++)

You can have a look on the overview on generators on this page.

A basic generator example

A basic full generator can be created easily :

 public class MyFullGenerator extends SourceBase
       implements Generator {
    int currentIndex = 0;
    int edgeId = 0;

    public void begin() {

    public boolean nextEvents() {
       return true;
    public void end() {
       // Nothing to do
    protected void addNode() {
       sendNodeAdded(sourceId, Integer.toString(currentIndex));
       for(int i = 0; i < currentIndex; i++)
          sendEdgeAdded(sourceId, Integer.toString(edgeId++),
                Integer.toString(i), Integer.toString(currentIndex), false);