001/**
002 * Copyright (c) 2011, The University of Southampton and the individual contributors.
003 * All rights reserved.
004 *
005 * Redistribution and use in source and binary forms, with or without modification,
006 * are permitted provided that the following conditions are met:
007 *
008 *   *  Redistributions of source code must retain the above copyright notice,
009 *      this list of conditions and the following disclaimer.
010 *
011 *   *  Redistributions in binary form must reproduce the above copyright notice,
012 *      this list of conditions and the following disclaimer in the documentation
013 *      and/or other materials provided with the distribution.
014 *
015 *   *  Neither the name of the University of Southampton nor the names of its
016 *      contributors may be used to endorse or promote products derived from this
017 *      software without specific prior written permission.
018 *
019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
029 */
030package org.openimaj.knn;
031
032/**
033 * Interface for K-nearest-neighbour implementations that are able to search
034 * directly using an indexed item of their own internal data as the query.
035 * 
036 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
037 * 
038 * @param <DISTANCES>
039 *            The type of distances measured (usually an array type)
040 */
041public interface InternalNearestNeighbours<DISTANCES> {
042        /**
043         * Search for the nearest neighbour to each of the N queries (given by their
044         * index in this nearest neighbours object), and return the index of each
045         * nearest neighbour and the respective distance.
046         * <p>
047         * <strong>This method should not return the same index as the query (i.e.
048         * technically it should find the second-nearest-neighbour)</strong>
049         * <p>
050         * For efficiency, to use this method, you need to pre-construct the arrays
051         * for storing the results outside of the method and pass them in as
052         * arguments.
053         * 
054         * @param qus
055         *            An array of N query vectors
056         * @param nnIndices
057         *            The return N-dimensional array for holding the indices of the
058         *            nearest neighbour of each respective query.
059         * @param nnDistances
060         *            The return N-dimensional array for holding the distances of
061         *            the nearest neighbour to each respective query.
062         */
063        public abstract void searchNN(final int[] qus, int[] nnIndices, DISTANCES nnDistances);
064
065        /**
066         * Search for the K nearest neighbours to each of the N queries, and return
067         * the indices of each nearest neighbour and their respective distances.
068         * <p>
069         * <strong>This method should not return the same index as the query (i.e.
070         * technically it should find the second-nearest-neighbour as the first
071         * returned value)</strong>
072         * <p>
073         * For efficiency, to use this method, you need to pre-construct the arrays
074         * for storing the results outside of the method and pass them in as
075         * arguments.
076         * 
077         * @param qus
078         *            An array of N query indices
079         * @param K
080         *            the number of neighbours to find
081         * @param nnIndices
082         *            The return N*K-dimensional array for holding the indices of
083         *            the K nearest neighbours of each respective query.
084         * @param nnDistances
085         *            The return N*K-dimensional array for holding the distances of
086         *            the nearest neighbours of each respective query.
087         */
088        public abstract void searchKNN(final int[] qus, int K, int[][] nnIndices, DISTANCES[] nnDistances);
089}