package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2011
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.HashMap;
import java.util.List;
import java.util.Map;
import de.lmu.ifi.dbs.elki.database.ids.DBID;
import de.lmu.ifi.dbs.elki.database.ids.DBIDUtil;
import de.lmu.ifi.dbs.elki.database.ids.ModifiableDBIDs;
import de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery;
import de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction;
import de.lmu.ifi.dbs.elki.distance.distancevalue.Distance;
import de.lmu.ifi.dbs.elki.index.tree.TreeIndexHeader;
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.persistent.PageFile;
import de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNHeap;
/**
* Abstract class for all M-Tree variants supporting processing of reverse
* k-nearest neighbor queries by using the k-nn distances of the entries, where
* k is less than or equal to the given parameter.
*
* @author Elke Achtert
*
* @apiviz.has MkTreeHeader oneway
*
* @param <O> the type of DatabaseObject to be stored in the metrical index
* @param <D> the type of Distance used in the metrical index
* @param <N> the type of MetricalNode used in the metrical index
* @param <E> the type of MetricalEntry used in the metrical index
*/
public abstract class AbstractMkTreeUnified<O, D extends Distance<D>, N extends AbstractMTreeNode<O, D, N, E>, E extends MTreeEntry<D>> extends AbstractMkTree<O, D, N, E> {
/**
* Holds the maximum value of k to support.
*/
private int k_max;
/**
* Constructor.
*
* @param pagefile Page file
* @param distanceQuery Distance query
* @param distanceFunction Distance function
* @param k_max Maximum value for k
*/
public AbstractMkTreeUnified(PageFile<N> pagefile, DistanceQuery<O, D> distanceQuery, DistanceFunction<O, D> distanceFunction, int k_max) {
super(pagefile, distanceQuery, distanceFunction);
this.k_max = k_max;
}
/**
* @return a new {@link MkTreeHeader}
*/
@Override
protected TreeIndexHeader createHeader() {
return new MkTreeHeader(getPageSize(), dirCapacity, leafCapacity, k_max);
}
@Override
public void insertAll(List<E> entries) {
if(entries.size() <= 0) {
return;
}
if(!initialized) {
initialize(entries.get(0));
}
Map<DBID, KNNHeap<D>> knnLists = new HashMap<DBID, KNNHeap<D>>();
ModifiableDBIDs ids = DBIDUtil.newArray(entries.size());
// insert sequentially
for(E entry : entries) {
// create knnList for the object
final DBID id = entry.getRoutingObjectID();
ids.add(id);
knnLists.put(id, new KNNHeap<D>(k_max, getDistanceFactory().infiniteDistance()));
// insert the object
super.insert(entry, false);
}
// do batch nn
batchNN(getRoot(), ids, knnLists);
// adjust the knn distances
kNNdistanceAdjustment(getRootEntry(), knnLists);
if(extraIntegrityChecks) {
getRoot().integrityCheck(this, getRootEntry());
}
}
/**
* Performs a distance adjustment in the subtree of the specified root entry.
*
* @param entry the root entry of the current subtree
* @param knnLists a map of knn lists for each leaf entry
*/
protected abstract void kNNdistanceAdjustment(E entry, Map<DBID, KNNHeap<D>> knnLists);
/**
* Get the value of k_max.
*
* @return k_max value.
*/
public int getKmax() {
return k_max;
}
}