Package de.lmu.ifi.dbs.elki.logging.progress

Examples of de.lmu.ifi.dbs.elki.logging.progress.IndefiniteProgress

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   */
  public Clustering<Model> run(Database database, Relation<O> relation) {
    SimilarityQuery<O, IntegerDistance> snnInstance = similarityFunction.instantiate(relation);

    FiniteProgress objprog = logger.isVerbose() ? new FiniteProgress("SNNClustering", relation.size(), logger) : null;
    IndefiniteProgress clusprog = logger.isVerbose() ? new IndefiniteProgress("Number of clusters", logger) : null;
    resultList = new ArrayList<ModifiableDBIDs>();
    noise = DBIDUtil.newHashSet();
    processedIDs = DBIDUtil.newHashSet(relation.size());
    if(relation.size() >= minpts) {
      for(DBID id : snnInstance.getRelation().iterDBIDs()) {
        if(!processedIDs.contains(id)) {
          expandCluster(snnInstance, id, objprog, clusprog);
          if(processedIDs.size() == relation.size() && noise.size() == 0) {
            break;
          }
        }
        if(objprog != null && clusprog != null) {
          objprog.setProcessed(processedIDs.size(), logger);
          clusprog.setProcessed(resultList.size(), logger);
        }
      }
    }
    else {
      for(DBID id : snnInstance.getRelation().iterDBIDs()) {
        noise.add(id);
        if(objprog != null && clusprog != null) {
          objprog.setProcessed(noise.size(), logger);
          clusprog.setProcessed(resultList.size(), logger);
        }
      }
    }
    // Finish progress logging
    if(objprog != null && clusprog != null) {
      objprog.ensureCompleted(logger);
      clusprog.setCompleted(logger);
    }

    Clustering<Model> result = new Clustering<Model>("Shared-Nearest-Neighbor Clustering", "snn-clustering");
    for(Iterator<ModifiableDBIDs> resultListIter = resultList.iterator(); resultListIter.hasNext();) {
      result.addCluster(new Cluster<Model>(resultListIter.next(), ClusterModel.CLUSTER));
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    this.lambda = lambda;
  }

  public Clustering<Model> run(Database database, Relation<V> relation) throws IllegalStateException {
    FiniteProgress objprog = getLogger().isVerbose() ? new FiniteProgress("Processing objects", relation.size(), getLogger()) : null;
    IndefiniteProgress clusprog = getLogger().isVerbose() ? new IndefiniteProgress("Number of clusters", getLogger()) : null;
    resultList = new ArrayList<ModifiableDBIDs>();
    noise = DBIDUtil.newHashSet();
    processedIDs = DBIDUtil.newHashSet(relation.size());

    LocallyWeightedDistanceFunction.Instance<V> distFunc = distanceFunction.instantiate(relation);
    RangeQuery<V, DoubleDistance> rangeQuery = database.getRangeQuery(distFunc);

    if(relation.size() >= minpts) {
      for(DBID id : relation.iterDBIDs()) {
        if(!processedIDs.contains(id)) {
          expandCluster(distFunc, rangeQuery, id, objprog, clusprog);
          if(processedIDs.size() == relation.size() && noise.size() == 0) {
            break;
          }
        }
        if(objprog != null && clusprog != null) {
          objprog.setProcessed(processedIDs.size(), getLogger());
          clusprog.setProcessed(resultList.size(), getLogger());
        }
      }
    }
    else {
      for(DBID id : relation.iterDBIDs()) {
        noise.add(id);
        if(objprog != null && clusprog != null) {
          objprog.setProcessed(processedIDs.size(), getLogger());
          clusprog.setProcessed(resultList.size(), getLogger());
        }
      }
    }

    if(objprog != null && clusprog != null) {
      objprog.setProcessed(processedIDs.size(), getLogger());
      clusprog.setProcessed(resultList.size(), getLogger());
    }

    Clustering<Model> result = new Clustering<Model>(getLongResultName(), getShortResultName());
    for(Iterator<ModifiableDBIDs> resultListIter = resultList.iterator(); resultListIter.hasNext();) {
      Cluster<Model> c = new Cluster<Model>(resultListIter.next(), ClusterModel.CLUSTER);
      result.addCluster(c);
    }

    Cluster<Model> n = new Cluster<Model>(noise, true, ClusterModel.CLUSTER);
    result.addCluster(n);

    if(objprog != null && clusprog != null) {
      objprog.setProcessed(processedIDs.size(), getLogger());
      clusprog.setProcessed(resultList.size(), getLogger());
    }
    // Signal that the progress has completed.
    if(objprog != null && clusprog != null) {
      objprog.ensureCompleted(getLogger());
      clusprog.setCompleted(getLogger());
    }
    return result;
  }
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  public Clustering<Model> run(Relation<O> relation) {
    RangeQuery<O, D> rangeQuery = QueryUtil.getRangeQuery(relation, getDistanceFunction());
    final int size = relation.size();

    FiniteProgress objprog = logger.isVerbose() ? new FiniteProgress("Processing objects", size, logger) : null;
    IndefiniteProgress clusprog = logger.isVerbose() ? new IndefiniteProgress("Number of clusters", logger) : null;
    resultList = new ArrayList<ModifiableDBIDs>();
    noise = DBIDUtil.newHashSet();
    processedIDs = DBIDUtil.newHashSet(size);
    if(size >= minpts) {
      for(DBID id : relation.iterDBIDs()) {
        if(!processedIDs.contains(id)) {
          expandCluster(relation, rangeQuery, id, objprog, clusprog);
        }
        if(objprog != null && clusprog != null) {
          objprog.setProcessed(processedIDs.size(), logger);
          clusprog.setProcessed(resultList.size(), logger);
        }
        if(processedIDs.size() == size) {
          break;
        }
      }
    }
    else {
      for(DBID id : relation.iterDBIDs()) {
        noise.add(id);
        if(objprog != null && clusprog != null) {
          objprog.setProcessed(noise.size(), logger);
          clusprog.setProcessed(resultList.size(), logger);
        }
      }
    }
    // Finish progress logging
    if(objprog != null) {
      objprog.ensureCompleted(logger);
    }
    if(clusprog != null) {
      clusprog.setCompleted(logger);
    }

    Clustering<Model> result = new Clustering<Model>("DBSCAN Clustering", "dbscan-clustering");
    for(ModifiableDBIDs res : resultList) {
      Cluster<Model> c = new Cluster<Model>(res, ClusterModel.CLUSTER);
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Related Classes of de.lmu.ifi.dbs.elki.logging.progress.IndefiniteProgress

  • de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedDBSCAN
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.LMCLUS
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS
  • de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN
  • de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering
  • de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS
  • de.lmu.ifi.dbs.elki.algorithm.KNNJoin
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