/*******************************************************************************
* Copyright (c) 2010 Haifeng Li
*
* 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 smile.neighbor;
/**
* The object encapsulates the results of nearest neighbor search. A returned
* neighbor for nearest neighbor search contains the key of object (say weight
* vector of a neuron) and the object itself (say a neuron in neural network,
* which also contains other information beyond weight vector), an index of
* object in the dataset, which is often useful, and the distance between
* the query key to the object key.
*
* @param <K> the type of keys.
* @param <V> the type of associated objects.
*
* @author Haifeng Li
*/
public class Neighbor<K, V> implements Comparable<Neighbor<K,V>> {
/**
* The key of neighbor.
*/
public K key;
/**
* The data object of neighbor. It may be same as the key object.
*/
public V value;
/**
* The index of neighbor object in the dataset.
*/
public int index;
/**
* The distance between the query and the neighbor.
*/
public double distance;
/**
* Constructor.
* @param object the neighbor object.
* @param index the index of neighbor object in the dataset.
* @param distance the distance between the query and the neighbor.
*/
public Neighbor(K key, V object, int index, double distance) {
this.key = key;
this.value = object;
this.index = index;
this.distance = distance;
}
@Override
public int compareTo(Neighbor<K,V> o) {
int d = (int) Math.signum(distance - o.distance);
// Sometime, the dataset contains duplicate samples.
// If the distances are same, we sort by the sample index.
if (d == 0)
return index - o.index;
else
return d;
}
}