Examples of de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress.ensureCompleted()

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

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

Examples of de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress.ensureCompleted()

de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress.ensureCompleted()
Ensure that the progress was completed, to make progress bars disappear @param logger Logger to report to.

      if(progress != null) {
        progress.incrementProcessed(logger);
      }
    }
    if(progress != null) {
      progress.ensureCompleted(logger);
    }


    if(logger.isVerbose()) {
      logger.verbose("Computing median error.");
    }

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      if(progressPreproc != null) {
        progressPreproc.incrementProcessed(logger);
      }
    }
    if(progressPreproc != null) {
      progressPreproc.ensureCompleted(logger);
    }
    // LOCI main step
    FiniteProgress progressLOCI = logger.isVerbose() ? new FiniteProgress("LOCI scores", relation.size(), logger) : null;
    WritableDoubleDataStore mdef_norm = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC);
    WritableDoubleDataStore mdef_radius = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC);

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      if(progressLOCI != null) {
        progressLOCI.incrementProcessed(logger);
      }
    }
    if(progressLOCI != null) {
      progressLOCI.ensureCompleted(logger);
    }
    Relation<Double> scoreResult = new MaterializedRelation<Double>("LOCI normalized MDEF", "loci-mdef-outlier", TypeUtil.DOUBLE, mdef_norm, relation.getDBIDs());
    OutlierScoreMeta scoreMeta = new QuotientOutlierScoreMeta(minmax.getMin(), minmax.getMax(), Double.POSITIVE_INFINITY, 0.0);
    OutlierResult result = new OutlierResult(scoreMeta, scoreResult);
    result.addChildResult(new MaterializedRelation<Double>("LOCI MDEF Radius", "loci-critical-radius", TypeUtil.DOUBLE, mdef_radius, relation.getDBIDs()));

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        if(prog != null) {
          prog.incrementProcessed(logger);
        }
      }
      if(prog != null) {
        prog.ensureCompleted(logger);
      }
    }


    WritableDoubleDataStore scores = DataStoreUtil.makeDoubleStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC);
    DoubleMinMax minmax = new DoubleMinMax();

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        if(cprog != null) {
          cprog.incrementProcessed(logger);
        }
      }
      if(cprog != null) {
        cprog.ensureCompleted(logger);
      }
    }
    else {
      FiniteProgress cprog = logger.isVerbose() ? new FiniteProgress("Combining results", relation.size(), logger) : null;
      for(DBID id : relation.iterDBIDs()) {

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        if(cprog != null) {
          cprog.incrementProcessed(logger);
        }
      }
      if(cprog != null) {
        cprog.ensureCompleted(logger);
      }
    }
    OutlierScoreMeta meta = new BasicOutlierScoreMeta(minmax.getMin(), minmax.getMax());
    Relation<Double> scoreres = new MaterializedRelation<Double>("Feature bagging", "fb-outlier", TypeUtil.DOUBLE, scores, relation.getDBIDs());
    return new OutlierResult(meta, scoreres);

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        if(progress != null) {
          progress.incrementProcessed(logger);
        }
      }
      if(progress != null) {
        progress.ensureCompleted(logger);
      }


      return store;
    }

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      if(progressOFlags != null) {
        progressOFlags.setProcessed(counter, logger);
      }
    }
    if(progressOFlags != null) {
      progressOFlags.ensureCompleted(logger);
    }
    return scores;
  }


  @Override

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        }
      }
    }
    // Finish progress logging
    if(objprog != null) {
      objprog.ensureCompleted(logger);
    }
    if(clusprog != null) {
      clusprog.setCompleted(logger);
    }

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      noiseDim = DatabaseUtil.dimensionality(relation);


      FiniteProgress progress = logger.isVerbose() ? new FiniteProgress("CASH Clustering", relation.size(), logger) : null;
      Clustering<Model> result = doRun(relation, progress);
      if(progress != null) {
        progress.ensureCompleted(logger);
      }


      if(logger.isVerbose()) {
        StringBuffer msg = new StringBuffer();
        for(Cluster<Model> c : result.getAllClusters()) {

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