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*/
/**
 * 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
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package org.openimaj.ml.clustering.assignment.soft;

import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;

import org.openimaj.ml.clustering.assignment.HardAssigner;
import org.openimaj.ml.clustering.assignment.SoftAssigner;
import org.openimaj.ml.clustering.assignment.hard.ExactDoubleAssigner;
import org.openimaj.ml.clustering.CentroidsProvider;
import org.openimaj.ml.clustering.kmeans.HierarchicalDoubleKMeansResult;
import org.openimaj.ml.clustering.kmeans.HierarchicalDoubleKMeansResult.Node;
import org.openimaj.util.pair.IndependentPair;
import org.openimaj.util.pair.IntDoublePair;

/**
 * A {@link SoftAssigner} for gathering the clusters assigned
 * to a point from a hierarchical clustering. The returned clusters
 * represent the path down the tree to the final closest leaf node.
 * 
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 */
public class HierarchicalDoublePathAssigner implements SoftAssigner<double[], double[]> {
        protected HierarchicalDoubleKMeansResult result;
        protected Map<CentroidsProvider<double[]>, HardAssigner<double[], double[], IntDoublePair>> assigners;
        
        /**
         * Construct with the given {@link HierarchicalDoubleKMeansResult} instance.
         * @param result the {@link HierarchicalDoubleKMeansResult} instance.
         */
        public HierarchicalDoublePathAssigner(HierarchicalDoubleKMeansResult result) {
                this.result = result;
                assigners = new HashMap<CentroidsProvider<double[]>, HardAssigner<double[], double[], IntDoublePair>>();
        }
        
        @Override
        public int[][] assign(double[][] data) {
                int[][] assignments = new int[data.length][result.getDepth()];
                
                for (int i = 0; i < data.length; i++) {
                        Node node = result.getRoot();
                        
                        int d = 0;
                        while (node != null) {
                                HardAssigner<double[], double[], IntDoublePair> assigner = assigners.get(node.result);
                                
                                if (assigner == null) {
                                        assigner = new ExactDoubleAssigner(node.result);
                                        assigners.put(node.result, assigner);
                                }
                                
                                int best = assigner.assign(data[i]);

                                assignments[i][d] = best;
                                ++d;

                                if (node.children == null)
                                        break;
                                node = node.children[best];
                        }
                }
                
                return assignments;
        }

        @Override
        public int[] assign(double[] data) {
                return assign(new double[][] {data})[0];
        }

        @Override
        public void assignWeighted(double[][] data, int[][] assignments, double[][] weights) {
                int depth = result.getDepth();
                
                for (int i = 0; i < data.length; i++) {
                        Node node = result.getRoot();
                        
                        if (assignments[i].length != depth)
                                assignments[i] = new int[depth];
                        Arrays.fill(assignments, -1);
                        
                        if (weights[i].length != depth)
                                weights[i] = new double[depth];
                        
                        int d = 0;
                        while (node != null) {
                                HardAssigner<double[], double[], IntDoublePair> assigner = assigners.get(node.result);
                                
                                if (assigner == null) {
                                        assigner = new ExactDoubleAssigner(node.result);
                                        assigners.put(node.result, assigner);
                                }
                                
                                IntDoublePair best = assigner.assignDistance(data[i]);
                                
                                assignments[i][d] = best.first;
                                weights[i][d] = best.second;
                                ++d;

                                if (node.children == null)
                                        break;
                                
                                node = node.children[best.first];
                        }
                }
        }

        @Override
        public IndependentPair<int[], double[]> assignWeighted(double[] data) {
                int[][] assignments = new int[1][];
                double[][] weights = new double[1][];
                
                assignWeighted(new double[][] { data }, assignments, weights);
                
                return new IndependentPair<int[], double[]>(assignments[0], weights[0]);
        }
        
        @Override
        public int numDimensions() {
            return result.numDimensions();
        }
        
        @Override
        public int size() {
            return result.numClusters();
        }
}