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

    }
    ArrayDBIDs rkNN_ids = updateKNNsAfterInsertion(ids);


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


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

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  protected void objectsRemoved(DBIDs ids) {
    StepProgress stepprog = getLogger().isVerbose() ? new StepProgress(3) : null;


    // delete the materialized (old) kNNs
    if(stepprog != null) {
      stepprog.beginStep(1, "New deletions ocurred, remove their materialized kNNs.", getLogger());
    }
    for(DBID id : ids) {
      storage.delete(id);
    }

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      storage.delete(id);
    }


    // update the affected kNNs
    if(stepprog != null) {
      stepprog.beginStep(2, "New deletions ocurred, update the affected kNNs.", getLogger());
    }
    ArrayDBIDs rkNN_ids = updateKNNsAfterDeletion(ids);


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

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    }
    ArrayDBIDs rkNN_ids = updateKNNsAfterDeletion(ids);


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


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

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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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    // Probabilistic distances
    WritableDoubleDataStore pdists = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP);
    {// computing PRDs
      if(stepprog != null) {
        stepprog.beginStep(3, "Computing pdists", logger);
      }
      FiniteProgress prdsProgress = logger.isVerbose() ? new FiniteProgress("pdists", relation.size(), logger) : null;
      for(DBID id : relation.iterDBIDs()) {
        final KNNResult<D> neighbors = knnReach.getKNNForDBID(id, kreach);
        double sqsum = 0.0;

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    // Compute PLOF values.
    WritableDoubleDataStore plofs = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP);
    MeanVariance mvplof = new MeanVariance();
    {// compute LOOP_SCORE of each db object
      if(stepprog != null) {
        stepprog.beginStep(4, "Computing PLOF", logger);
      }


      FiniteProgress progressPLOFs = logger.isVerbose() ? new FiniteProgress("PLOFs for objects", relation.size(), logger) : null;
      for(DBID id : relation.iterDBIDs()) {
        final KNNResult<D> neighbors = knnComp.getKNNForDBID(id, kcomp);

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    // Compute final LoOP values.
    WritableDoubleDataStore loops = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC);
    {// compute LOOP_SCORE of each db object
      if(stepprog != null) {
        stepprog.beginStep(5, "Computing LoOP scores", logger);
      }


      FiniteProgress progressLOOPs = logger.isVerbose() ? new FiniteProgress("LoOP for objects", relation.size(), logger) : null;
      for(DBID id : relation.iterDBIDs()) {
        loops.putDouble(id, NormalDistribution.erf((plofs.doubleValue(id) - 1) / (nplof * sqrt2)));

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