package jcgp.backend.modules.ea;

import jcgp.backend.modules.mutator.Mutator;
import jcgp.backend.population.Population;
import jcgp.backend.resources.Resources;
import jcgp.backend.resources.parameters.BooleanParameter;
import jcgp.backend.resources.parameters.IntegerParameter;
import jcgp.backend.resources.parameters.Parameter;
import jcgp.backend.resources.parameters.ParameterStatus;

/**
 * (μ + λ) EA.
 * 
 * 
 * @author Eduardo Pedroni
 *
 */
public class MuPlusLambda implements EvolutionaryAlgorithm {
	
	private int fittestChromosome;
	
	private IntegerParameter parents, offspring;
	private BooleanParameter report;
		
	public MuPlusLambda(final Resources resources) {
		parents = new IntegerParameter(1, "Parents") {
			@Override
			public void validate(int newValue) {
				if (newValue + offspring.get() != resources.getInt("popSize")) {
					status = ParameterStatus.INVALID;
					status.setDetails("Parents + offspring must equal population size.");
				} else if (newValue <= 0) {
					status = ParameterStatus.INVALID;
					status.setDetails("EA needs at least 1 parent.");
				} else {
					status = ParameterStatus.VALID;
				}
			}
		};
		offspring = new IntegerParameter(4, "Offspring") {
			@Override
			public void validate(int newValue) {
				if (newValue + parents.get() != resources.getInt("popSize")) {
					status = ParameterStatus.INVALID;
					status.setDetails("Parents + offspring must equal population size.");
				} else if (newValue <= 0) {
					status = ParameterStatus.INVALID;
					status.setDetails("EA needs at least 1 offspring.");
				} else {
					status = ParameterStatus.VALID;
				}
			}
		};
		report = new BooleanParameter(false, "Report") {
			@Override
			public void validate(boolean newValue) {
				// nothing
			}
		};
	}

	@Override
	public void evolve(Population population, Mutator mutator, Resources resources) {
		// select fittest chromosomes
		fittestChromosome = 0;
		
		for (int i = 1; i < resources.getInt("popSize"); i++) {
			if (population.getChromosome(i).getFitness() >= population.getChromosome(fittestChromosome).getFitness()) {
				fittestChromosome = i;
			}
		}
		
		// create copies of fittest chromosome, mutate them
		for (int i = 0; i < resources.getInt("popSize"); i++) {
			if (i != fittestChromosome) {
				population.copyChromosome(fittestChromosome, i);
				mutator.mutate(population.getChromosome(i), resources);
			}
		}
		
	}

	@Override
	public int getFittestChromosome() {
		return fittestChromosome;
	}

	@Override
	public Parameter[] getLocalParameters() {
		return new Parameter[] {parents, offspring, report};
	}

	@Override
	public String toString() {
		return "(μ + λ)";
	}
	
}