/*
* Copyright (c) 2012-2014, Peter Abeles. All Rights Reserved.
*
* This file is part of DDogleg (http://ddogleg.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.ddogleg.nn.wrap;
import org.ddogleg.nn.NearestNeighbor;
import org.ddogleg.nn.NnData;
import org.ddogleg.nn.alg.*;
import org.ddogleg.struct.FastQueue;
import java.util.List;
/**
* K-D tree search which searches through multiple trees. The search is performed using a Best-Bin-First approach
*
* @author Peter Abeles
*/
public class KdForestBbfSearch implements NearestNeighbor {
// set of K-D trees which are to be searched
KdTree[]forest;
// creates the set of K-D trees given the same input
KdTreeConstructor constructor;
KdTreeSearch1Bbf search1;
KdTreeSearchNBbf searchN;
AxisSplitter splitter;
KdTreeMemory memory = new KdTreeMemory();
// storage for multiple results
FastQueue found = new FastQueue(KdTreeResult.class,true);
public KdForestBbfSearch(int numberOfTrees,
int maxNodesSearched,
AxisSplitter splitter) {
this.forest = new KdTree[ numberOfTrees ];
this.splitter = splitter;
this.search1 = new KdTreeSearch1Bbf(maxNodesSearched);
this.searchN = new KdTreeSearchNBbf(maxNodesSearched);
}
@Override
public void init(int pointDimension) {
constructor = new KdTreeConstructor(memory,pointDimension,splitter);
}
@Override
public void setPoints(List points, List data) {
if( forest[0] != null ) {
for( int i = 0; i < forest.length; i++ )
memory.recycleGraph(forest[i]);
}
for( int i = 0; i < forest.length; i++ )
forest[i] = constructor.construct(points,data);
search1.setTrees(forest);
searchN.setTrees(forest);
}
@Override
public boolean findNearest(double[] point, double maxDistance, NnData result) {
if( maxDistance < 0 )
search1.setMaxDistance(Double.MAX_VALUE);
else
search1.setMaxDistance(maxDistance);
KdTree.Node found = search1.findNeighbor(point);
if( found == null )
return false;
result.point = found.point;
result.data = (D)found.data;
result.distance = search1.getDistance();
return true;
}
@Override
public void findNearest(double[] point, double maxDistance, int numNeighbors, FastQueue> result) {
if( maxDistance <= 0 )
searchN.setMaxDistance(Double.MAX_VALUE);
else
searchN.setMaxDistance(maxDistance);
found.reset();
searchN.findNeighbor(point, numNeighbors, found);
for( int i = 0; i < found.size; i++ ) {
KdTreeResult k = found.get(i);
NnData r = result.grow();
r.point = k.node.point;
r.data = (D)k.node.data;
r.distance = k.distance;
}
}
}
Ads help maintain this website.