/**
 * 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.ml.clustering.kmeans;

import gnu.trove.list.array.TIntArrayList;
import gnu.trove.procedure.TIntProcedure;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.Arrays;
import java.util.Scanner;

import org.openimaj.feature.DoubleFVComparison;
import org.openimaj.ml.clustering.CentroidsProvider;
import org.openimaj.ml.clustering.Clusters;
import org.openimaj.ml.clustering.SpatialClusterer;
import org.openimaj.ml.clustering.SpatialClusters;
import org.openimaj.ml.clustering.assignment.HardAssigner;
import org.openimaj.ml.clustering.assignment.hard.ExactDoubleAssigner;
import org.openimaj.util.pair.IntDoublePair;

/**
 * The result of a {@link SpatialClusterer} that just produces a flat set of
 * centroids.
 *
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 */
public class SphericalKMeansResult implements SpatialClusters<double[]>, CentroidsProvider<double[]> {
        final static String HEADER = Clusters.CLUSTER_HEADER + "SpKM";

        /** The centroids of the clusters */
        public double[][] centroids;

        /** The assignments of the training data to clusters */
        public int[] assignments;

        @Override
        public boolean equals(Object obj) {
                if (!(obj instanceof SphericalKMeansResult))
                        return false;

                final SphericalKMeansResult other = (SphericalKMeansResult) obj;
                for (int i = 0; i < this.centroids.length; i++) {
                        if (!Arrays.equals(this.centroids[i], other.centroids[i]))
                                return false;
                }
                return true;
        }

        @Override
        public String asciiHeader() {
                return "ASCII" + HEADER;
        }

        @Override
        public byte[] binaryHeader() {
                return HEADER.getBytes();
        }

        @Override
        public void readASCII(Scanner br) throws IOException {
                // Read Header
                final int K = Integer.parseInt(br.nextLine().trim());
                final int M = Integer.parseInt(br.nextLine().trim());

                centroids = new double[K][M];
                for (int k = 0; k < K; k++) {
                        final String[] parts = br.nextLine().split(",");

                        for (int d = 0; d < M; d++) {
                                centroids[k][d] = Double.parseDouble(parts[d]);
                        }
                }

                final int A = Integer.parseInt(br.nextLine().trim());
                assignments = new int[A];
                for (int a = 0; a < A; a++) {
                        assignments[a] = Integer.parseInt(br.nextLine().trim());
                }
        }

        @Override
        public void readBinary(DataInput in) throws IOException {
                final int K = in.readInt();
                final int M = in.readInt();

                centroids = new double[K][M];

                for (int k = 0; k < K; k++) {
                        for (int d = 0; d < M; d++) {
                                centroids[k][d] = in.readDouble();
                        }
                }

                final int A = in.readInt();
                assignments = new int[A];
                for (int a = 0; a < A; a++) {
                        assignments[a] = in.readInt();
                }
        }

        @Override
        public void writeASCII(PrintWriter writer) throws IOException {
                writer.println(centroids.length);
                writer.println(centroids[0].length);

                for (int k = 0; k < centroids.length; k++) {
                        for (int d = 0; d < centroids[0].length; d++) {
                                writer.print(centroids[k][d] + ",");
                        }
                        writer.println();
                }

                writer.println(assignments.length);
                for (int a = 0; a < assignments.length; a++) {
                        writer.println(assignments[a]);
                }
        }

        @Override
        public void writeBinary(DataOutput out) throws IOException {
                out.writeInt(centroids.length);
                out.writeInt(centroids[0].length);

                for (int k = 0; k < centroids.length; k++) {
                        for (int d = 0; d < centroids[0].length; d++) {
                                out.writeDouble(centroids[k][d]);
                        }
                }

                out.writeInt(assignments.length);
                for (int a = 0; a < assignments.length; a++) {
                        out.writeInt(assignments[a]);
                }
        }

        @Override
        public String toString() {
                String str = "";
                str += "DoubleCentroidsResult" + "\n";
                str += "No. of Clusters: " + centroids.length + "\n";
                str += "No. of Dimensions: " + centroids[0].length + "\n";
                return str;
        }

        @Override
        public double[][] getCentroids() {
                return this.centroids;
        }

        @Override
        public HardAssigner<double[], double[], IntDoublePair> defaultHardAssigner() {
                return new ExactDoubleAssigner(this, DoubleFVComparison.INNER_PRODUCT);
        }

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

        @Override
        public int numClusters() {
                return centroids.length;
        }

        /**
         * Compute the histogram of number of assignments to each cluster
         *
         * @return the histogram
         */
        public int[] getAssignmentHistogram() {
                final int[] hist = new int[centroids.length];

                for (int i = 0; i < assignments.length; i++) {
                        hist[assignments[i]]++;
                }

                return hist;
        }

        /**
         * Filter the cluster centroids be removing those with less than threshold
         * items
         *
         * @param threshold
         *            minimum number of items
         * @return the filtered clusters
         */
        public double[][] filter(int threshold) {
                final int[] hist = getAssignmentHistogram();
                final TIntArrayList toKeep = new TIntArrayList();
                for (int i = 0; i < hist.length; i++) {
                        if (hist[i] > threshold) {
                                toKeep.add(i);
                        }
                }

                final double[][] fcen = new double[toKeep.size()][];
                toKeep.forEach(new TIntProcedure() {
                        int i = 0;

                        @Override
                        public boolean execute(int value) {
                                fcen[i++] = centroids[value];
                                return true;
                        }
                });

                return fcen;
        }
}