Examples of de.lmu.ifi.dbs.elki.logging.progress.StepProgress.beginStep()

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

Class de.lmu.ifi.dbs.elki.logging.progress.StepProgress

Examples of de.lmu.ifi.dbs.elki.logging.progress.StepProgress.beginStep()

de.lmu.ifi.dbs.elki.logging.progress.StepProgress.beginStep()
Do a new step. @param step Step number @param stepTitle Step title


    StepProgress stepprog = logger.isVerbose() ? new StepProgress(3) : null;


    // run COPAC
    if(stepprog != null) {
      stepprog.beginStep(1, "Preprocessing local correlation dimensionalities and partitioning data", logger);
    }
    Clustering<Model> copacResult = copacAlgorithm.run(relation);


    DistanceQuery<V, IntegerDistance> query = copacAlgorithm.getPartitionDistanceQuery();

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    DistanceQuery<V, IntegerDistance> query = copacAlgorithm.getPartitionDistanceQuery();


    // extract correlation clusters
    if(stepprog != null) {
      stepprog.beginStep(2, "Extract correlation clusters", logger);
    }
    SortedMap<Integer, List<Cluster<CorrelationModel<V>>>> clusterMap = extractCorrelationClusters(copacResult, relation, dimensionality);
    if(logger.isDebugging()) {
      StringBuffer msg = new StringBuffer("Step 2: Extract correlation clusters...");
      for(Integer corrDim : clusterMap.keySet()) {

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      logger.verbose(clusters + " clusters extracted.");
    }


    // build hierarchy
    if(stepprog != null) {
      stepprog.beginStep(3, "Building hierarchy", logger);
    }
    buildHierarchy(clusterMap, query);
    if(logger.isDebugging()) {
      StringBuffer msg = new StringBuffer("Step 3: Build hierarchy");
      for(Integer corrDim : clusterMap.keySet()) {

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    StepProgress stepprog = logger.isVerbose() ? new StepProgress(dimensionality) : null;


    // Generate all 1-dimensional clusters
    if(stepprog != null) {
      stepprog.beginStep(1, "Generate all 1-dimensional clusters.", logger);
    }


    // mapping of dimensionality to set of subspaces
    HashMap<Integer, List<Subspace<V>>> subspaceMap = new HashMap<Integer, List<Subspace<V>>>();

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    }


    // Generate (d+1)-dimensional clusters from d-dimensional clusters
    for(int d = 0; d < dimensionality - 1; d++) {
      if(stepprog != null) {
        stepprog.beginStep(d + 2, "Generate " + (d + 2) + "-dimensional clusters from " + (d + 1) + "-dimensional clusters.", logger);
      }


      List<Subspace<V>> subspaces = subspaceMap.get(d);
      if(subspaces == null || subspaces.isEmpty()) {
        if(stepprog != null) {

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      List<Subspace<V>> subspaces = subspaceMap.get(d);
      if(subspaces == null || subspaces.isEmpty()) {
        if(stepprog != null) {
          for(int dim = d + 1; dim < dimensionality - 1; dim++) {
            stepprog.beginStep(dim + 2, "Generation of" + (dim + 2) + "-dimensional clusters not applicable, because no more " + (d + 2) + "-dimensional subspaces found.", logger);
          }
        }
        break;
      }

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    StepProgress stepprog = getLogger().isVerbose() ? new StepProgress(3) : null;


    ArrayDBIDs aids = DBIDUtil.ensureArray(ids);
    // materialize the new kNNs and RkNNs
    if(stepprog != null) {
      stepprog.beginStep(1, "New insertions ocurred, materialize their new kNNs and RkNNs.", getLogger());
    }
    materializeKNNAndRKNNs(aids, null);


    // update the old kNNs and RkNNs
    if(stepprog != null) {

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    }
    materializeKNNAndRKNNs(aids, null);


    // update the old kNNs and RkNNs
    if(stepprog != null) {
      stepprog.beginStep(2, "New insertions ocurred, update the affected kNNs and RkNNs.", getLogger());
    }
    ArrayDBIDs rkNN_ids = updateKNNsAndRkNNs(ids);


    // inform listener
    if(stepprog != null) {

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    }
    ArrayDBIDs rkNN_ids = updateKNNsAndRkNNs(ids);


    // inform listener
    if(stepprog != null) {
      stepprog.beginStep(3, "New insertions ocurred, inform listeners.", getLogger());
    }
    fireKNNsInserted(ids, rkNN_ids);


    if(stepprog != null) {
      stepprog.ensureCompleted(getLogger());

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    StepProgress stepprog = getLogger().isVerbose() ? new StepProgress(3) : null;


    ArrayDBIDs aids = DBIDUtil.ensureArray(ids);
    // delete the materialized (old) kNNs and RkNNs
    if(stepprog != null) {
      stepprog.beginStep(1, "New deletions ocurred, remove their materialized kNNs and RkNNs.", getLogger());
    }
    List<List<DistanceResultPair<D>>> kNNs = new ArrayList<List<DistanceResultPair<D>>>(ids.size());
    List<List<DistanceResultPair<D>>> rkNNs = new ArrayList<List<DistanceResultPair<D>>>(ids.size());
    for(DBID id : aids) {
      kNNs.add(storage.get(id));

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