de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split
Class MLBDistSplit<O,D extends Distance<D>,N extends AbstractMTreeNode<O,D,N,E>,E extends MTreeEntry<D>>

java.lang.Object
  de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split.MTreeSplit<O,D,N,E>
      de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split.MLBDistSplit<O,D,N,E>

Type Parameters:

O - the type of DatabaseObject to be stored in the M-Tree

D - the type of Distance used in the M-Tree

N - the type of AbstractMTreeNode used in the M-Tree

E - the type of MetricalEntry used in the M-Tree

public class MLBDistSplit<O,D extends Distance<D>,N extends AbstractMTreeNode<O,D,N,E>,E extends MTreeEntry<D>>
extends MTreeSplit<O,D,N,E>

Encapsulates the required methods for a split of a node in an M-Tree. The routing objects are chosen according to the M_LB_DIST strategy.

Field Summary

Fields inherited from class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split.MTreeSplit

assignments

Constructor Summary

MLBDistSplit(N node, DistanceQuery<O,D> distanceFunction)
Creates a new split object.

Method Summary

private void

promote(N node, DistanceQuery<O,D> distanceFunction) Selects the second object of the specified node to be promoted and stored into the parent node and partitions the entries according to the M_LB_DIST strategy.

Methods inherited from class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split.MTreeSplit

balancedPartition, getAssignments

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

MLBDistSplit

public MLBDistSplit(N node,
                    DistanceQuery<O,D> distanceFunction)

Creates a new split object.

Parameters:

node - the node to be split

distanceFunction - the distance function

Method Detail

promote

private void promote(N node,
                     DistanceQuery<O,D> distanceFunction)

Selects the second object of the specified node to be promoted and stored into the parent node and partitions the entries according to the M_LB_DIST strategy.

This strategy considers all possible pairs of objects and chooses the pair of objects for which the distance is maximum.

Parameters:

node - the node to be split

distanceFunction - the distance function