package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split;

/*
 This file is part of ELKI:
 Environment for Developing KDD-Applications Supported by Index-Structures

 Copyright (C) 2013
 Ludwig-Maximilians-Universität München
 Lehr- und Forschungseinheit für Datenbanksysteme
 ELKI Development Team

 This program is free software: you can redistribute it and/or modify
 it under the terms of the GNU Affero General Public License as published by
 the Free Software Foundation, either version 3 of the License, or
 (at your option) any later version.

 This program is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 GNU Affero General Public License for more details.

 You should have received a copy of the GNU Affero General Public License
 along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

import java.util.ArrayList;
import java.util.Collections;
import java.util.List;

import de.lmu.ifi.dbs.elki.database.ids.DBID;
import de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery;
import de.lmu.ifi.dbs.elki.distance.distancevalue.Distance;
import de.lmu.ifi.dbs.elki.index.tree.DistanceEntry;
import de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeNode;
import de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.MTreeEntry;
import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;

/**
 * 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.
 * 
 * Reference:
 * <p>
 * P. Ciaccia, M. Patella, P. Zezula<br />
 * M-tree: An Efficient Access Method for Similarity Search in Metric Spaces<br />
 * In Proceedings of 23rd International Conference on Very Large Data Bases
 * (VLDB'97), August 25-29, 1997, Athens, Greece
 * </p>
 * 
 * @author Elke Achtert
 * 
 * @param <O> the type of DatabaseObject to be stored in the M-Tree
 * @param <D> the type of Distance used in the M-Tree
 * @param <N> the type of AbstractMTreeNode used in the M-Tree
 * @param <E> the type of MetricalEntry used in the M-Tree
 */
@Reference(authors = "P. Ciaccia, M. Patella, P. Zezula", title = "M-tree: An Efficient Access Method for Similarity Search in Metric Spaces", booktitle = "VLDB'97, Proceedings of 23rd International Conference on Very Large Data Bases, August 25-29, 1997, Athens, Greece", url = "http://www.vldb.org/conf/1997/P426.PDF")
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> {
  /**
   * Creates a new split object.
   * 
   * @param node the node to be split
   * @param distanceFunction the distance function
   */
  public MLBDistSplit() {
    super();
  }

  /**
   * 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.
   * <p/>
   * This strategy considers all possible pairs of objects and chooses the pair
   * of objects for which the distance is maximum.
   * 
   * @param node the node to be split
   * @param distanceFunction the distance function
   */
  @Override
  public Assignments<D, E> split(N node, DistanceQuery<O, D> distanceFunction) {
    DBID firstPromoted = null;
    DBID secondPromoted = null;

    // choose first and second routing object
    D currentMaxDist = distanceFunction.nullDistance();
    for (int i = 0; i < node.getNumEntries(); i++) {
      DBID id1 = node.getEntry(i).getRoutingObjectID();
      for (int j = i + 1; j < node.getNumEntries(); j++) {
        DBID id2 = node.getEntry(j).getRoutingObjectID();

        D distance = distanceFunction.distance(id1, id2);
        if (distance.compareTo(currentMaxDist) >= 0) {
          firstPromoted = id1;
          secondPromoted = id2;
          currentMaxDist = distance;
        }
      }
    }

    // partition the entries
    List<DistanceEntry<D, E>> list1 = new ArrayList<>();
    List<DistanceEntry<D, E>> list2 = new ArrayList<>();
    for (int i = 0; i < node.getNumEntries(); i++) {
      DBID id = node.getEntry(i).getRoutingObjectID();
      D d1 = distanceFunction.distance(firstPromoted, id);
      D d2 = distanceFunction.distance(secondPromoted, id);

      list1.add(new DistanceEntry<>(node.getEntry(i), d1, i));
      list2.add(new DistanceEntry<>(node.getEntry(i), d2, i));
    }
    Collections.sort(list1);
    Collections.sort(list2);

    return balancedPartition(node, firstPromoted, secondPromoted, distanceFunction);
  }
}

@@ -967,90 +967,8 @@
 */%0A%0A
-import java.util.ArrayList;%0Aimport java.util.Collections;%0Aimport java.util.List;%0A%0A
 impo
@@ -1139,61 +1139,8 @@
 ce;%0A
-import de.lmu.ifi.dbs.elki.index.tree.DistanceEntry;%0A
 impo
@@ -3869,570 +3869,8 @@
  %7D%0A%0A
-    // partition the entries%0A    List%3CDistanceEntry%3CD, E%3E%3E list1 = new ArrayList%3C%3E();%0A    List%3CDistanceEntry%3CD, E%3E%3E list2 = new ArrayList%3C%3E();%0A    for (int i = 0; i %3C node.getNumEntries(); i++) %7B%0A      DBID id = node.getEntry(i).getRoutingObjectID();%0A      D d1 = distanceFunction.distance(firstPromoted, id);%0A      D d2 = distanceFunction.distance(secondPromoted, id);%0A%0A      list1.add(new DistanceEntry%3C%3E(node.getEntry(i), d1, i));%0A      list2.add(new DistanceEntry%3C%3E(node.getEntry(i), d2, i));%0A    %7D%0A    Collections.sort(list1);%0A    Collections.sort(list2);%0A%0A
     

Drop code without side effects, that was repeated in super class.