package org.java.evolutionary.sequence;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Set;

import ec.EvolutionState;
import ec.Individual;
import ec.Statistics;
import ec.gp.GPIndividual;
import ec.util.Parameter;

/**
 * This class is meant for getting plugin for HallOfFame. 
 * By using this we get hook when evaluations are done, we try
 * to rank the Individuals based on fitness.
 * It uses size using the parameter hall-of-fame and writes the
 * top individuals to hall-of-fame-file parameter value file.
 * This can then be used for interpretation.
 * @author udaykamath
 *
 */
public class StatisticPluginForHallofFame extends Statistics {
	private HallOfFame hallOfFame;
	private int sizeOfHallOfFame;
	private String fileName;
	
	public void setup(final EvolutionState state, final Parameter base) {
		// DO NOT FORGET to call super.setup(...) !!
		super.setup(state, base);
		//read the hall of fame count
		String sizeofHallOfFame = state.parameters.getString(base
				.push("hall-of-fame"), null);
		sizeOfHallOfFame = new Integer(sizeofHallOfFame).intValue();
		fileName = state.parameters.getString(base
				.push("hall-of-fame-file"), null);
		hallOfFame = new HallOfFame();
		hallOfFame.setup(fileName);
	}
	
	public void postEvaluationStatistics(final EvolutionState state) {
		System.out.println("Generation.." + state.generation);
		//get the individuals
		Individual[] individuals = state.population.subpops[0].individuals;
		//now create a map of individuals and fitness
		Map<GPIndividual,Double> individualsToFitness = new HashMap<GPIndividual,Double>();
		for(int i=0; i< individuals.length; i++){
			individualsToFitness.put((GPIndividual)individuals[i], new Double(individuals[i].fitness.fitness()));
		}
		//sort the map
		Map<GPIndividual,Double> results = sortByValue(individualsToFitness);
		GPIndividual[] allInds = results.keySet().toArray(new GPIndividual[0]);
		int size = sizeOfHallOfFame;
		if(state.generation == 0)
			size =6000;
		hallOfFame.addTopPopulationToHallOfFame(state, allInds, size);		
	}
	
	public void finalStatistics(final EvolutionState state, final int result) {
		hallOfFame.flushToFile(state,fileName);
	}
	
	private Map<GPIndividual,Double> sortByValue(Map<GPIndividual,Double> map) {
	     List list = new LinkedList(map.entrySet());
	     Collections.sort(list, new Comparator() {
	          public int compare(Object o1, Object o2) {
	        	 double d1 = (Double)((Map.Entry) (o1)).getValue();
	        	 double d2 = (Double)((Map.Entry) (o2)).getValue();
	        	 int returnval =0;
	     		if (d1 < d2)
	     	            returnval= 1;		 // Neither val is NaN, thisVal is smaller
	     	    if (d1 > d2)
	     	            returnval= -1;		 // Neither val is NaN, thisVal is larger
	     	    if(d1 == d2)
	     	    	returnval= 0;
	     	    return returnval;
	          }
	     });

	    Map<GPIndividual,Double> result = new LinkedHashMap<GPIndividual,Double>();
	    for (Iterator it = list.iterator(); it.hasNext();) {
	        Map.Entry entry = (Map.Entry)it.next();
	        result.put((GPIndividual)entry.getKey(), (Double)entry.getValue());
	    }
	    return result;
	} 
	
	
	

}