Ejemplo n.º 1
0
  public Graph createGraph(Clustering[] clusts) {
    Clustering c = clusts[0];
    // total number of items
    int n = c.instancesCount();

    Graph graph = new AdjListGraph();
    Object2LongOpenHashMap<Instance> mapping = new Object2LongOpenHashMap();

    Instance a, b;
    Node na, nb;
    // cluster membership
    int ca, cb;
    int x = 0;
    Edge edge;
    // accumulate evidence
    for (Clustering clust : clusts) {
      System.out.println("reducing " + (x++));
      for (int i = 1; i < n; i++) {
        a = clust.instance(i);
        na = fetchNode(graph, mapping, a);
        ca = clust.assignedCluster(a.getIndex());
        for (int j = 0; j < i; j++) {
          b = clust.instance(j);
          nb = fetchNode(graph, mapping, b);
          // for each pair of instances check if placed in the same cluster
          cb = clust.assignedCluster(b.getIndex());
          if (ca == cb) {
            edge = graph.getEdge(na, nb);
            // check if exists
            if (edge == null) {
              edge = graph.getFactory().newEdge(na, nb, 0, 0, false);
              graph.addEdge(edge);
            }
            // increase weight by 1
            edge.setWeight(edge.getWeight() + 1.0);
          }
        }
      }
    }
    return graph;
  }
Ejemplo n.º 2
0
 @Override
 public Clustering updateCutoff(double cutoff) {
   this.cutoff = cutoff;
   int[] assign = new int[dataset.size()];
   int estClusters = (int) Math.sqrt(dataset.size());
   colorGenerator.reset();
   num = 0; // human readable
   Clustering clusters = new ClusterList(estClusters);
   DendroNode root = treeData.getRoot();
   if (root != null) {
     checkCutoff(root, cutoff, clusters, assign);
     if (clusters.size() > 0) {
       mapping = assign;
     } else {
       LOG.info("failed to cutoff dendrogram, cut = {}", cutoff);
     }
   }
   // add input dataset to clustering lookup
   if (noise != null) {
     Cluster clust = new BaseCluster<>(noise.size());
     clust.setColor(colorGenerator.next());
     clust.setClusterId(num++);
     clust.setParent(getDataset());
     clust.setName("Noise");
     clust.setAttributes(getDataset().getAttributes());
     for (Instance ins : noise) {
       clust.add(ins);
       mapping[ins.getIndex()] = num - 1;
     }
     clusters.add(clust);
   }
   clusters.lookupAdd(dataset);
   if (dendroMapping != null) {
     clusters.lookupAdd(dendroMapping);
   }
   clusters.lookupAdd(this);
   return clusters;
 }