/*
        AUTOMATICALLY GENERATED BY jTemp FROM
        /Users/jsh2/Work/openimaj/target/checkout/machine-learning/nearest-neighbour/src/main/jtemp/org/openimaj/knn/#T#NearestNeighboursExact.jtemp
*/
/**
 * Copyright (c) 2011, The University of Southampton and the individual contributors.
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification,
 * are permitted provided that the following conditions are met:
 *
 *   *  Redistributions of source code must retain the above copyright notice,
 *      this list of conditions and the following disclaimer.
 *
 *   *  Redistributions in binary form must reproduce the above copyright notice,
 *      this list of conditions and the following disclaimer in the documentation
 *      and/or other materials provided with the distribution.
 *
 *   *  Neither the name of the University of Southampton nor the names of its
 *      contributors may be used to endorse or promote products derived from this
 *      software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
package org.openimaj.knn;

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

import org.openimaj.feature.ShortFVComparison;
import org.openimaj.feature.ShortFVComparator;
import org.openimaj.util.pair.IntFloatPair;
import org.openimaj.util.queue.BoundedPriorityQueue;

/**
 * Exact (brute-force) k-nearest-neighbour implementation.
 * 
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
 */
public class ShortNearestNeighboursExact extends ShortNearestNeighbours {
    /**
         * {@link NearestNeighboursFactory} for producing
         * {@link ShortNearestNeighboursExact}s.
         * 
         * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
         */
    public static final class Factory implements NearestNeighboursFactory<ShortNearestNeighboursExact, short[]> {
        private final ShortFVComparator distance;
        
        /**
         * Construct the factory using Euclidean distance for the 
         * produced ShortNearestNeighbours instances.
         */
        public Factory() {
            this.distance = null;
        }
        
        /**
         * Construct the factory with the given distance function
         * for the produced ShortNearestNeighbours instances.
         * 
                 * @param distance
                 *            the distance function
         */
        public Factory(ShortFVComparator distance) {
            this.distance = distance;
        }
        
        @Override
        public ShortNearestNeighboursExact create(short[][] data) {
            return new ShortNearestNeighboursExact(data, distance);
        }
    }
    
        protected final short[][] pnts;
        protected final ShortFVComparator distance;

        /**
         * Construct the ShortNearestNeighboursExact over the provided
         * dataset and using Euclidean distance.
         * @param pnts the dataset
         */
        public ShortNearestNeighboursExact(final short [][] pnts) {
                this(pnts, null);
        }

        /**
         * Construct the ShortNearestNeighboursExact over the provided
         * dataset with the given distance function. 
         * <p>
         * Note: If the distance function provides similarities rather
         * than distances they are automatically inverted.
         *  
         * @param pnts the dataset
         * @param distance the distance function
         */
        public ShortNearestNeighboursExact(final short [][] pnts, final ShortFVComparator distance) {
                this.pnts = pnts;
                this.distance = distance;
        }
        
        @Override
        public void searchNN(final short [][] qus, int [] indices, float [] distances) {
                final int N = qus.length;
                
                final BoundedPriorityQueue<IntFloatPair> queue =
                                new BoundedPriorityQueue<IntFloatPair>(1, IntFloatPair.SECOND_ITEM_ASCENDING_COMPARATOR);

        //prepare working data
                List<IntFloatPair> list = new ArrayList<IntFloatPair>(2);
                list.add(new IntFloatPair());
                list.add(new IntFloatPair());
                
                for (int n=0; n < N; ++n) {
                        List<IntFloatPair> result = search(qus[n], queue, list);
                        
                        final IntFloatPair p = result.get(0);
                        indices[n] = p.first;
                        distances[n] = p.second;
                }
        }

        @Override
        public void searchKNN(final short [][] qus, int K, int [][] indices, float [][] distances) {
                // Fix for when the user asks for too many points.
                K = Math.min(K, pnts.length);

                final int N = qus.length;

                final BoundedPriorityQueue<IntFloatPair> queue =
                                new BoundedPriorityQueue<IntFloatPair>(K, IntFloatPair.SECOND_ITEM_ASCENDING_COMPARATOR);

        //prepare working data
                List<IntFloatPair> list = new ArrayList<IntFloatPair>(K + 1);
                for (int i = 0; i < K + 1; i++) {
                        list.add(new IntFloatPair());
                }

        // search on each query
                for (int n = 0; n < N; ++n) {
                        List<IntFloatPair> result = search(qus[n], queue, list);
                        
                        for (int k = 0; k < K; ++k) {
                                final IntFloatPair p = result.get(k);
                                indices[n][k] = p.first;
                                distances[n][k] = p.second;
                        }
                }
        }
        
        @Override
        public void searchNN(final List<short[]> qus, int [] indices, float [] distances) {
                final int N = qus.size();
                
                final BoundedPriorityQueue<IntFloatPair> queue =
                                new BoundedPriorityQueue<IntFloatPair>(1, IntFloatPair.SECOND_ITEM_ASCENDING_COMPARATOR);

        //prepare working data
                List<IntFloatPair> list = new ArrayList<IntFloatPair>(2);
                list.add(new IntFloatPair());
                list.add(new IntFloatPair());
                
                for (int n=0; n < N; ++n) {
                        List<IntFloatPair> result = search(qus.get(n), queue, list);
                        
                        final IntFloatPair p = result.get(0);
                        indices[n] = p.first;
                        distances[n] = p.second;
                }
        }

        @Override
        public void searchKNN(final List<short[]> qus, int K, int [][] indices, float [][] distances) {
                // Fix for when the user asks for too many points.
                K = Math.min(K, pnts.length);

                final int N = qus.size();

                final BoundedPriorityQueue<IntFloatPair> queue =
                                new BoundedPriorityQueue<IntFloatPair>(K, IntFloatPair.SECOND_ITEM_ASCENDING_COMPARATOR);

        //prepare working data
                List<IntFloatPair> list = new ArrayList<IntFloatPair>(K + 1);
                for (int i = 0; i < K + 1; i++) {
                        list.add(new IntFloatPair());
                }

        // search on each query
                for (int n = 0; n < N; ++n) {
                        List<IntFloatPair> result = search(qus.get(n), queue, list);
                        
                        for (int k = 0; k < K; ++k) {
                                final IntFloatPair p = result.get(k);
                                indices[n][k] = p.first;
                                distances[n][k] = p.second;
                        }
                }
        }

    @Override
        public List<IntFloatPair> searchKNN(short[] query, int K) {
                // Fix for when the user asks for too many points.
                K = Math.min(K, pnts.length);

                final BoundedPriorityQueue<IntFloatPair> queue =
                                new BoundedPriorityQueue<IntFloatPair>(K, IntFloatPair.SECOND_ITEM_ASCENDING_COMPARATOR);

        //prepare working data
                List<IntFloatPair> list = new ArrayList<IntFloatPair>(K + 1);
                for (int i = 0; i < K + 1; i++) {
                        list.add(new IntFloatPair());
                }

        // search
        return search(query, queue, list);
        }

        @Override
        public IntFloatPair searchNN(final short[] query) {
                final BoundedPriorityQueue<IntFloatPair> queue =
                                new BoundedPriorityQueue<IntFloatPair>(1, IntFloatPair.SECOND_ITEM_ASCENDING_COMPARATOR);

        //prepare working data
                List<IntFloatPair> list = new ArrayList<IntFloatPair>(2);
                list.add(new IntFloatPair());
                list.add(new IntFloatPair());
                
                return search(query, queue, list).get(0);
        }

    private List<IntFloatPair> search(short[] query, BoundedPriorityQueue<IntFloatPair> queue, List<IntFloatPair> results) {
        IntFloatPair wp = null;
        
        // reset all values in the queue to MAX, -1
                for (final IntFloatPair p : results) {
                        p.second = Float.MAX_VALUE;
                        p.first = -1;
                        wp = queue.offerItem(p);
                }

        // perform the search
                for (int i = 0; i < this.pnts.length; i++) {
                        wp.second = distanceFunc(distance, query, pnts[i]);
                        wp.first = i;
                        wp = queue.offerItem(wp);
                }
                
        return queue.toOrderedListDestructive();
    }

        @Override
        public int numDimensions() {
                return pnts[0].length;
        }

        @Override
        public int size() {
                return pnts.length;
        }
        
        /**
         * Get the underlying data points.
         * 
         * @return the data points
         */
        public short[][] getPoints() {
                return this.pnts;
        }

        /**
         * Compute the distance between two vectors using the underlying distance
         * comparison used by this class.
         * 
         * @param a
         *            the first vector
         * @param b
         *            the second vector
         * @return the distance between the two vectors
         */
        public float computeDistance(short[] a, short[] b) {
                if (distance == null)
                        return (float) ShortFVComparison.SUM_SQUARE.compare(a, b);
                return (float) distance.compare(a, b);
        }

        /**
         * Get the distance comparator
         * 
         * @return the distance comparator
         */
        public ShortFVComparator distanceComparator() {
                return this.distance;
        }
}