Package de.lmu.ifi.dbs.elki.distance.distancevalue

Examples of de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance.compareTo()

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          DBID pid = ((LeafEntry) p).getDBID();
          // FIXME: objects are NOT accessible by DBID in a plain rtree context!
          DoubleDistance dist_pq = distanceFunction.distance(relation.get(pid), relation.get(q));
          tree.distanceCalcs++;
          if(dist_pq.compareTo(knn_q_maxDist) <= 0) {
            knns_q.add(dist_pq, pid);
          }
        }
      }
    }
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      for(DBID m_i : medoids) {
        if(m_i == m) {
          continue;
        }
        DoubleDistance currentDist = distFunc.distance(m, m_i);
        if(minDist == null || currentDist.compareTo(minDist) < 0) {
          minDist = currentDist;
        }
      }

      // determine points in sphere centered at m with radius minDist
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      for(int i = 0; i < dimensions.size(); i++) {
        Pair<V, Set<Integer>> pair_i = dimensions.get(i);
        V c_i = pair_i.first;
        Set<Integer> dimensions_i = pair_i.second;
        DoubleDistance currentDist = manhattanSegmentalDistance(p, c_i, dimensions_i);
        if(minDist == null || currentDist.compareTo(minDist.first) < 0) {
          minDist = new Pair<DoubleDistance, Integer>(currentDist, i);
        }
      }
      // add p to cluster with mindist
      assert minDist != null;
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    ids.addDBIDs(interval.getIDs());
    // Search for nearby vectors in original database
    for(DBID id : relation.iterDBIDs()) {
      DoubleVector v = new DoubleVector(relation.get(id).getColumnVector().getArrayRef());
      DoubleDistance d = df.distance(v, centroid);
      if(d.compareTo(eps) < 0) {
        ids.add(id);
      }
    }

    Matrix basis = model.getStrongEigenvectors();
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          DBID pid = ((LeafEntry) p).getDBID();
          // FIXME: objects are NOT accessible by DBID in a plain rtree context!
          DoubleDistance dist_pq = distanceFunction.distance(relation.get(pid), relation.get(q));
          tree.distanceCalcs++;
          if(dist_pq.compareTo(knn_q_maxDist) <= 0) {
            knns_q.add(dist_pq, pid);
          }
        }
      }
    }
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      for(DBID m_i : medoids) {
        if(m_i == m) {
          continue;
        }
        DoubleDistance currentDist = distFunc.distance(m, m_i);
        if(minDist == null || currentDist.compareTo(minDist) < 0) {
          minDist = currentDist;
        }
      }

      // determine points in sphere centered at m with radius minDist
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      for(int i = 0; i < dimensions.size(); i++) {
        Pair<V, Set<Integer>> pair_i = dimensions.get(i);
        V c_i = pair_i.first;
        Set<Integer> dimensions_i = pair_i.second;
        DoubleDistance currentDist = manhattanSegmentalDistance(p, c_i, dimensions_i);
        if(minDist == null || currentDist.compareTo(minDist.first) < 0) {
          minDist = new Pair<DoubleDistance, Integer>(currentDist, i);
        }
      }
      // add p to cluster with mindist
      assert minDist != null;
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    ids.addDBIDs(interval.getIDs());
    // Search for nearby vectors in original database
    for(DBID id : relation.iterDBIDs()) {
      DoubleVector v = new DoubleVector(relation.get(id).getColumnVector().getArrayRef());
      DoubleDistance d = df.distance(v, centroid);
      if(d.compareTo(eps) < 0) {
        ids.add(id);
      }
    }

    Matrix basis = model.getStrongEigenvectors();
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