/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2014 by RapidMiner and the contributors
 *
 *  Complete list of developers available at our web site:
 *
 *       http://rapidminer.com
 *
 *  This program is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU Affero General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This program is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU Affero General Public License for more details.
 *
 *  You should have received a copy of the GNU Affero General Public License
 *  along with this program.  If not, see http://www.gnu.org/licenses/.
 */
package com.rapidminer.operator.features.construction;

import java.util.Iterator;
import java.util.LinkedList;
import java.util.List;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.Tools;
import com.rapidminer.example.set.AttributeWeightedExampleSet;
import com.rapidminer.generator.AttributePeak;
import com.rapidminer.generator.FeatureGenerator;
import com.rapidminer.generator.GenerationException;
import com.rapidminer.generator.SinusFactory;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.tools.RandomGenerator;


/**
 * The mutation operator for FourierGGA. This operator adds single attributes
 * from the original set, creates new ones and deselect single attributes. For
 * each freshly added attribute a fourier generation will will be performed.
 * 
 * @see FourierGGA
 * @author Ingo Mierswa
 *          ingomierswa Exp $
 */
public class FourierGeneratingMutation extends ExampleSetBasedIndividualOperator {

	private List<FeatureGenerator> generators;

	private List<Attribute> originalAttributes;

	private double p;

	private int numberOfConstructed;

	private int numberOfOriginal;

	private SinusFactory factory = null;

	private String[] unusableFunctions = new String[0];

	private RandomGenerator random;

	public FourierGeneratingMutation(List<Attribute> originalAttributes, double p, List<FeatureGenerator> generators, int numberOfConstructed, int numberOfOriginal, int maxPeaks, int adaptionType, int attributesPerPeak, double epsilon, String[] unusableFunctions, RandomGenerator random) {
		this.originalAttributes = originalAttributes;
		this.p = p;
		this.generators = generators;
		this.numberOfConstructed = numberOfConstructed;
		this.numberOfOriginal = numberOfOriginal;
		this.factory = new SinusFactory(maxPeaks);
		this.factory.setAdaptionType(adaptionType);
		this.factory.setEpsilon(epsilon);
		this.factory.setAttributePerPeak(attributesPerPeak);
		this.unusableFunctions = unusableFunctions;
        this.random = random;
	}

	/**
	 * Performs one of the following three mutations:
	 * <ul>
	 * <li>add a newly generated attribute</li>
	 * <li>add an original attribute</li>
	 * <li>remove an attribute</li>
	 * </ul>
	 */
	@Override
	public List<ExampleSetBasedIndividual> operate(ExampleSetBasedIndividual individual) throws Exception {
		LinkedList<ExampleSetBasedIndividual> l = new LinkedList<ExampleSetBasedIndividual>();
		AttributeWeightedExampleSet clone = (AttributeWeightedExampleSet) individual.getExampleSet().clone();

		try {
			int numberOriginal = addOriginalAttribute(clone);
			int numberCreated = addGeneratedAttribute(clone);
			deselect(clone, numberOriginal + numberCreated);
		} catch (GenerationException e) {
			individual.getExampleSet().getLog().logWarning("GeneratingMutation: Exception occured during generation of attributes, using only original example set instead.");
		}

		if (clone.getNumberOfUsedAttributes() > 0) {
			l.add(new ExampleSetBasedIndividual(clone));
		}
		l.add(individual);
		return l;
	}

	/** Adds a new attribute. Returns true, if generation was possible. */
	private int addGeneratedAttribute(AttributeWeightedExampleSet exampleSet) throws OperatorException {
		int counter = 0;
		for (int k = 0; k < numberOfConstructed; k++) {
			if (random.nextDouble() < p) {
				FeatureGenerator generator = FeatureGenerator.selectGenerator(exampleSet, generators, unusableFunctions, random);
				if (generator != null) {
					generator = generator.newInstance();
					Attribute[] args = Tools.getRandomCompatibleAttributes(exampleSet, generator, unusableFunctions, random);
					generator.setArguments(args);
					List<FeatureGenerator> generatorList = new LinkedList<FeatureGenerator>();
					generatorList.add(generator);

					List<Attribute> newAttributes = FeatureGenerator.generateAll(exampleSet.getExampleTable(), generatorList);
					for (Attribute newAttribute : newAttributes)
						exampleSet.getAttributes().addRegular(newAttribute);
					counter += newAttributes.size();

					Iterator<Attribute> i = newAttributes.iterator();
					List<AttributePeak> sinAttributes = new LinkedList<AttributePeak>();
					Attribute label = exampleSet.getAttributes().getLabel();
					while (i.hasNext()) {
						Attribute current = i.next();
						if (current.isNumerical() && (current.getConstruction().indexOf("sin") == -1)) {
							List<AttributePeak> peaks = factory.getAttributePeaks(exampleSet, label, current);
							sinAttributes.addAll(peaks);
						}
					}

					if (sinAttributes.size() > 0)
						factory.generateSinusFunctions(exampleSet, sinAttributes, random);
					counter += sinAttributes.size();
				}
			}
		}
		return counter;
	}

	private int addOriginalAttribute(AttributeWeightedExampleSet exampleSet) throws GenerationException, OperatorException {
		int counter = 0;
		for (int k = 0; k < numberOfOriginal; k++) {
			if (random.nextDouble() < p) {
				int i = random.nextInt(originalAttributes.size());
				Attribute originalAttribute = originalAttributes.get(i);
				if (exampleSet.getAttributes().getRegular(originalAttribute.getName()) == null) {
					exampleSet.getAttributes().addRegular(originalAttribute);
					counter++;
				}

				// add sinus functions of the original attribute
				List<AttributePeak> peaks = factory.getAttributePeaks(exampleSet, exampleSet.getAttributes().getLabel(), originalAttribute);
				if (peaks.size() > 0)
					factory.generateSinusFunctions(exampleSet, peaks, random);
				counter += peaks.size();
			}
		}
		return counter;
	}

	private void deselect(AttributeWeightedExampleSet exampleSet, int numberNew) {
		double[] probs = Tools.getInverseProbabilitiesFromWeights(exampleSet.getAttributes().createRegularAttributeArray(), exampleSet);
		Iterator<Attribute> i = exampleSet.getAttributes().iterator();
		int index = 0;
		while (i.hasNext()) {
			i.next();
			if (random.nextDouble() < p * probs[index++] * numberNew) {
				i.remove();
			}
		}
	}
}