/**
 * 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.experiment.evaluation.classification.analysers.confusionmatrix;

import gov.sandia.cognition.learning.performance.categorization.ConfusionMatrix;

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

import net.sf.jasperreports.engine.JasperPrint;

import org.apache.commons.math.stat.descriptive.DescriptiveStatistics;
import org.openimaj.experiment.evaluation.AnalysisResult;

import com.bethecoder.ascii_table.ASCIITable;

/**
 * Aggregated confusion matrix results
 * 
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 *
 * @param <CLASS> The type of the classes represented by the {@link CMResult}s
 */
public class AggregatedCMResult<CLASS> implements AnalysisResult {
        /**
         * Aggregated accuracy and error rate.
         * 
         * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
         */
        public static class AggregateStatistics {
                private double meanAccuracy;
                private double stddevAccuracy;
                
                private double meanErrorRate;
                private double stddevErrorRate;
        }
        
        protected List<CMResult<CLASS>> matrices;

        /**
         * Default constructor
         */
        public AggregatedCMResult() {
                this.matrices = new ArrayList<CMResult<CLASS>>();
        }
        
        /**
         * Construct with a list of results
         * @param results the results
         */
        public AggregatedCMResult(List<CMResult<CLASS>> results) {
                this.matrices = results;
        }

        /**
         * Compute the current aggregate statistics of the
         * accumulated results. 
         * 
         * @return the current aggregate statistics
         */
        public AggregateStatistics computeStatistics() {
                DescriptiveStatistics accuracy = new DescriptiveStatistics();
                DescriptiveStatistics errorRate = new DescriptiveStatistics();
                
                for (CMResult<CLASS> result : matrices) {
                        ConfusionMatrix<CLASS> m = result.getMatrix();
                        accuracy.addValue(m.getAccuracy());
                        errorRate.addValue(m.getErrorRate());
                }
                
                AggregateStatistics s = new AggregateStatistics();
                s.meanAccuracy = accuracy.getMean();
                s.stddevAccuracy = accuracy.getStandardDeviation();
                
                s.meanErrorRate = errorRate.getMean();
                s.stddevErrorRate = errorRate.getStandardDeviation();
                
                return s;
        }
        
        @Override
        public String toString() {
                return getSummaryReport();
        }

        @Override
        public JasperPrint getSummaryReport(String title, String info) {
                //FIXME:
                throw new UnsupportedOperationException();
        }

        @Override
        public JasperPrint getDetailReport(String title, String info) {
                //FIXME:
                throw new UnsupportedOperationException();
        }

        @Override
        public String getSummaryReport() {
                AggregateStatistics summary = computeStatistics();
                
                String [] header = {"Value", "Mean", "Standard Deviation"};
                String [][] data = {
                                { "Accuracy", String.format("%2.3f", summary.meanAccuracy), String.format("%2.3f", summary.stddevAccuracy) },
                                { "Error Rate", String.format("%2.3f", summary.meanErrorRate), String.format("%2.3f", summary.stddevErrorRate) }
                };
                
                return ASCIITable.getInstance().getTable(header, data);
        }

        @Override
        public String getDetailReport() {
                StringBuilder sb = new StringBuilder();
                
                sb.append("** Summary Report **\n");
                sb.append(getSummaryReport());
                sb.append("\n");
                sb.append("** Per Run Reports **\n");
                for (int i=0; i<this.matrices.size(); i++) {
                        CMResult<CLASS> result = this.matrices.get(i);
                        
                        
                        sb.append("***************************************************************\n");
                        sb.append("* Run #"+i+"\n");
                        sb.append("***************************************************************\n");
                        sb.append(result.getDetailReport());
                        sb.append("\n");
                }
                
                return sb.toString();
        }
}