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...main/java/i5/las2peer/services/ocd/algorithms/ParticleSwarmLabelPropagationAlgorithm.java
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| package i5.las2peer.services.ocd.algorithms; | ||
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| import i5.las2peer.services.ocd.algorithms.utils.OcdAlgorithmException; | ||
| import i5.las2peer.services.ocd.graphs.Cover; | ||
| import i5.las2peer.services.ocd.graphs.CoverCreationType; | ||
| import i5.las2peer.services.ocd.graphs.CustomGraph; | ||
| import i5.las2peer.services.ocd.graphs.GraphType; | ||
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| import java.util.*; | ||
| import java.util.stream.Collectors; | ||
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| import io.reactivex.internal.operators.flowable.FlowableOnErrorReturn; | ||
| import org.apache.jena.atlas.iterator.Iter; | ||
| import org.la4j.matrix.Matrix; | ||
| import org.la4j.matrix.dense.Basic2DMatrix; | ||
| import org.la4j.matrix.sparse.CCSMatrix; | ||
| import org.la4j.vector.Vector; | ||
| import org.la4j.vector.Vectors; | ||
| import org.la4j.vector.dense.BasicVector; | ||
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| import org.graphstream.graph.Graph; | ||
| import org.graphstream.graph.Node; | ||
| import org.graphstream.graph.Edge; | ||
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| public class ParticleSwarmLabelPropagationAlgorithm implements OcdAlgorithm { | ||
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| private int populationSize = 10; | ||
| private float initChance = 0.5f; | ||
| private float inertiaFactor = 0.5f; | ||
| private float learningFactor1 = 1; | ||
| private float learningFactor2 = 1; | ||
| private int maxIterations = 10; | ||
| private static Random rng; | ||
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| @Override | ||
| public CoverCreationType getAlgorithmType() { | ||
| return CoverCreationType.PSO_LPA_ALGORITHM; | ||
| } | ||
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| @Override | ||
| public Map<String, String> getParameters() { | ||
| return null; | ||
| } | ||
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| @Override | ||
| public void setParameters(Map<String, String> parameters) throws IllegalArgumentException { | ||
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| } | ||
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| @Override | ||
| public Set<GraphType> compatibleGraphTypes() { | ||
| Set<GraphType> compatibilities = new HashSet<GraphType>(); | ||
| return compatibilities; | ||
| } | ||
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| @Override | ||
| public Cover detectOverlappingCommunities(CustomGraph graph) { | ||
| return runLabelPropagation(graph,runParticleSwarmOptimization(graph)); | ||
| } | ||
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| private HashMap<String, Integer> runParticleSwarmOptimization(CustomGraph graph) { | ||
| int[] k = new int[1]; | ||
| HashMap<String, Integer>[] populationPosition = populationPositionInitialization(graph, k); | ||
| HashMap<String, Integer>[] populationVelocity = new HashMap[populationSize]; | ||
| HashMap<String, Integer>[] populationExperiencePosition = new HashMap[populationSize]; | ||
| float[] populationExperienceFitness = new float[populationSize]; | ||
| HashMap<String, Integer> optimalPosition; | ||
| float optimalFitness = -1; | ||
| int temp = 0; | ||
| for (int i = 0; i < populationSize; i++){ | ||
| populationVelocity[i] = new HashMap<>(); | ||
| populationExperiencePosition[i] = (HashMap<String, Integer>)populationPosition[i].clone(); | ||
| populationExperienceFitness[i] = calculateFitness(populationPosition[i]); | ||
| if (optimalFitness < populationExperienceFitness[i]) { | ||
| temp = i; | ||
| optimalFitness = populationExperienceFitness[i]; | ||
| } | ||
| } | ||
| optimalPosition = (HashMap<String, Integer>)populationPosition[temp].clone(); | ||
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| int iteration = 0; | ||
| while (maxIterations > iteration) { | ||
| updateVelocity(populationVelocity, populationPosition, populationExperiencePosition, optimalPosition, populationExperienceFitness); | ||
| updatePosition(populationVelocity, populationPosition, populationExperiencePosition, populationExperienceFitness, k); | ||
| temp = -1; | ||
| for (int i = 0; i < populationSize; i++){ | ||
| float fitness = calculateFitness(populationPosition[i]); | ||
| if (fitness > populationExperienceFitness[i]) { | ||
| populationExperienceFitness[i] = fitness; | ||
| populationExperiencePosition[i] = (HashMap<String, Integer>)populationPosition[i].clone(); | ||
| } | ||
| if (optimalFitness < populationExperienceFitness[i]) { | ||
| temp = i; | ||
| optimalFitness = populationExperienceFitness[i]; | ||
| } | ||
| } | ||
| if (temp >= 0) | ||
| optimalPosition = (HashMap<String, Integer>)populationPosition[temp].clone(); | ||
| } | ||
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| return optimalPosition; | ||
| } | ||
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| private HashMap<String, Integer>[] populationPositionInitialization(CustomGraph graph, int[] k) { | ||
| HashMap<String, Integer>[] populationPosition = new HashMap[populationSize]; | ||
| k[0] = 1; | ||
| for (int l = 0; l < populationSize; l++) { | ||
| populationPosition[l] = new HashMap<>(); | ||
| final int p = l; | ||
| Iterator<Node> iterator = graph.nodes().iterator(); | ||
| while (iterator.hasNext()) { | ||
| Node j = iterator.next(); | ||
| if (populationPosition[p].get(j.getId()) != 0) | ||
| continue; | ||
| HashMap<String, Integer> flag = new HashMap<>(); | ||
| List<Node> nodes = j.neighborNodes().toList(); | ||
| while (nodes.size() > 0) { | ||
| Node i = nodes.get(0); | ||
| nodes.remove(0); | ||
| if (flag.get(i.getId()) == 0 && populationPosition[p].get(i.getId()) == 0) { | ||
| flag.put(i.getId(), 1); | ||
| if (rng.nextFloat() > initChance) { | ||
| populationPosition[p].put(i.getId(), populationPosition[p].get(j.getId())); | ||
| nodes.addAll(i.neighborNodes().toList()); | ||
| } | ||
| } | ||
| } | ||
| k[0]++; | ||
| } | ||
| } | ||
| return populationPosition; | ||
| } | ||
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| private void updateVelocity(HashMap<String, Integer>[] velocity, HashMap<String, Integer>[] position, HashMap<String, Integer>[] expPosition, HashMap<String, Integer> optimalPosition, float[] expFitness){ | ||
| for (int i = 0; i < populationSize; i++) { | ||
| int p = i; | ||
| velocity[p].replaceAll((k,v)-> | ||
| (int)( | ||
| inertiaFactor*v + | ||
| learningFactor1*rng.nextFloat()*(expPosition[p].get(k) - position[p].get(k)) + | ||
| learningFactor2*rng.nextFloat()*(optimalPosition.get(k) - position[p].get(k))) | ||
| ); | ||
| } | ||
| } | ||
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| private void updatePosition(HashMap<String, Integer>[] velocity, HashMap<String, Integer>[] position, HashMap<String, Integer>[] expPosition, float[] expFitness, int[] kCount){ | ||
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| } | ||
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| private float calculateFitness(HashMap<String, Integer> position){ | ||
| return 0.5f; | ||
| } | ||
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| private Cover runLabelPropagation(CustomGraph graph, HashMap<String, Integer> initialization) { | ||
| return null; | ||
| } | ||
| } |
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.../java/i5/las2peer/services/ocd/algorithms/ParticleSwarmLabelPropagationAlgorithmTest.java
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,4 @@ | ||
| package i5.las2peer.services.ocd.algorithms; | ||
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| public class ParticleSwarmLabelPropagationAlgorithmTest { | ||
| } |