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 affected_lof_ids = mergeIDs(primDistRKNNs, affected_lrd_ids, insertions, updates1);
      recomputeLOFs(affected_lof_ids, lofResult);


      // fire result changed
      if(stepprog != null) {
        stepprog.beginStep(3, "Inform listeners.", logger);
      }
      lofResult.getResult().getHierarchy().resultChanged(lofResult.getResult());


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

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    private void kNNsRemoved(DBIDs deletions, DBIDs updates1, DBIDs updates2, LOFResult<O, D> lofResult) {
      StepProgress stepprog = logger.isVerbose() ? new StepProgress(4) : null;


      // delete lrds and lofs
      if(stepprog != null) {
        stepprog.beginStep(1, "Delete old LRDs and LOFs.", logger);
      }
      for(DBID id : deletions) {
        lofResult.getLrds().delete(id);
        lofResult.getLofs().delete(id);
      }

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        lofResult.getLofs().delete(id);
      }


      // recompute lrds
      if(stepprog != null) {
        stepprog.beginStep(2, "Recompute LRDs.", logger);
      }
      ArrayDBIDs lrd_ids = DBIDUtil.ensureArray(updates2);
      List<List<DistanceResultPair<D>>> reachDistRKNNs = lofResult.getRkNNReach().getRKNNForBulkDBIDs(lrd_ids, k);
      ArrayDBIDs affected_lrd_id_candidates = mergeIDs(reachDistRKNNs, lrd_ids);
      ArrayDBIDs affected_lrd_ids = DBIDUtil.newArray(affected_lrd_id_candidates.size());

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        }
      }


      // recompute lofs
      if(stepprog != null) {
        stepprog.beginStep(3, "Recompute LOFS.", logger);
      }
      List<List<DistanceResultPair<D>>> primDistRKNNs = lofResult.getRkNNRefer().getRKNNForBulkDBIDs(affected_lrd_ids, k);
      ArrayDBIDs affected_lof_ids = mergeIDs(primDistRKNNs, affected_lrd_ids, updates1);
      recomputeLOFs(affected_lof_ids, lofResult);

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      ArrayDBIDs affected_lof_ids = mergeIDs(primDistRKNNs, affected_lrd_ids, updates1);
      recomputeLOFs(affected_lof_ids, lofResult);


      // fire result changed
      if(stepprog != null) {
        stepprog.beginStep(4, "Inform listeners.", logger);
      }
      lofResult.getResult().getHierarchy().resultChanged(lofResult.getResult());


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

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    MeanVariance momax = new MeanVariance();
    MeanVariance modif = new MeanVariance();
    // Histogram
    final AggregatingHistogram<Pair<Long, Long>, Pair<Long, Long>> histogram;
    if(stepprog != null) {
      stepprog.beginStep(1, "Prepare histogram.", logger);
    }
    if(exact) {
      gminmax = exactMinMax(relation, distFunc);
      histogram = AggregatingHistogram.LongSumLongSumHistogram(numbin, gminmax.getMin(), gminmax.getMax());
    }

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    else {
      histogram = FlexiHistogram.LongSumLongSumHistogram(numbin);
    }


    if(stepprog != null) {
      stepprog.beginStep(2, "Build histogram.", logger);
    }
    final FiniteProgress progress = logger.isVerbose() ? new FiniteProgress("Distance computations", relation.size(), logger) : null;
    // iterate per cluster
    final Pair<Long, Long> incFirst = new Pair<Long, Long>(1L, 0L);
    final Pair<Long, Long> incSecond = new Pair<Long, Long>(0L, 1L);

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    // Probabilistic distances
    WritableDataStore<Double> pdists = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP, Double.class);
    {// 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()) {
        List<DistanceResultPair<D>> neighbors = knnReach.getKNNForDBID(id, kreach);
        double sqsum = 0.0;

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    // Compute PLOF values.
    WritableDataStore<Double> plofs = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP, Double.class);
    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()) {
        List<DistanceResultPair<D>> neighbors = knnComp.getKNNForDBID(id, kcomp);

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    // Compute final LoOP values.
    WritableDataStore<Double> loops = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC, Double.class);
    {// 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.put(id, MathUtil.erf((plofs.get(id) - 1) / (nplof * sqrt2)));

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