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A Java's Collaborative Filtering library to carry out experiments in research of Collaborative Filtering based Recommender Systems. The library has been designed from researchers to researchers.
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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.commons.math3.genetics;

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

import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NumberIsTooLargeException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.random.RandomGenerator;

/**
 * N-point crossover policy. For each iteration a random crossover point is
 * selected and the first part from each parent is copied to the corresponding
 * child, and the second parts are copied crosswise.
 *
 * Example (2-point crossover):
 *  * -C- denotes a crossover point
 *           -C-       -C-                         -C-        -C-
 * p1 = (1 0  | 1 0 0 1 | 0 1 1)    X    p2 = (0 1  | 1 0 1 0  | 1 1 1)
 *      \----/ \-------/ \-----/              \----/ \--------/ \-----/
 *        ||      (*)       ||                  ||      (**)       ||
 *        VV      (**)      VV                  VV      (*)        VV
 *      /----\ /--------\ /-----\             /----\ /--------\ /-----\
 * c1 = (1 0  | 1 0 1 0  | 0 1 1)    X   c2 = (0 1  | 1 0 0 1  | 0 1 1)
 * 
 *
 * This policy works only on {@link AbstractListChromosome}, and therefore it
 * is parameterized by T. Moreover, the chromosomes must have same lengths.
 *
 * @param  generic type of the {@link AbstractListChromosome}s for crossover
 * @since 3.1
 */
public class NPointCrossover implements CrossoverPolicy {

    /** The number of crossover points. */
    private final int crossoverPoints;

    /**
     * Creates a new {@link NPointCrossover} policy using the given number of points.
     * 
     * Note: the number of crossover points must be < chromosome length - 1.
     * This condition can only be checked at runtime, as the chromosome length is not known in advance.
     *
     * @param crossoverPoints the number of crossover points
     * @throws NotStrictlyPositiveException if the number of {@code crossoverPoints} is not strictly positive
     */
    public NPointCrossover(final int crossoverPoints) throws NotStrictlyPositiveException {
        if (crossoverPoints <= 0) {
            throw new NotStrictlyPositiveException(crossoverPoints);
        }
        this.crossoverPoints = crossoverPoints;
    }

    /**
     * Returns the number of crossover points used by this {@link CrossoverPolicy}.
     *
     * @return the number of crossover points
     */
    public int getCrossoverPoints() {
        return crossoverPoints;
    }

    /**
     * Performs a N-point crossover. N random crossover points are selected and are used
     * to divide the parent chromosomes into segments. The segments are copied in alternate
     * order from the two parents to the corresponding child chromosomes.
     *
     * Example (2-point crossover):
     * 
     * -C- denotes a crossover point
     *           -C-       -C-                         -C-        -C-
     * p1 = (1 0  | 1 0 0 1 | 0 1 1)    X    p2 = (0 1  | 1 0 1 0  | 1 1 1)
     *      \----/ \-------/ \-----/              \----/ \--------/ \-----/
     *        ||      (*)       ||                  ||      (**)       ||
     *        VV      (**)      VV                  VV      (*)        VV
     *      /----\ /--------\ /-----\             /----\ /--------\ /-----\
     * c1 = (1 0  | 1 0 1 0  | 0 1 1)    X   c2 = (0 1  | 1 0 0 1  | 0 1 1)
     * 
     *
     * @param first first parent (p1)
     * @param second second parent (p2)
     * @return pair of two children (c1,c2)
     * @throws MathIllegalArgumentException iff one of the chromosomes is
     *   not an instance of {@link AbstractListChromosome}
     * @throws DimensionMismatchException if the length of the two chromosomes is different
     */
    @SuppressWarnings("unchecked") // OK because of instanceof checks
    public ChromosomePair crossover(final Chromosome first, final Chromosome second)
        throws DimensionMismatchException, MathIllegalArgumentException {

        if (!(first instanceof AbstractListChromosome && second instanceof AbstractListChromosome)) {
            throw new MathIllegalArgumentException(LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME);
        }
        return mate((AbstractListChromosome) first, (AbstractListChromosome) second);
    }

    /**
     * Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover.
     *
     * @param first the first chromosome
     * @param second the second chromosome
     * @return the pair of new chromosomes that resulted from the crossover
     * @throws DimensionMismatchException if the length of the two chromosomes is different
     * @throws NumberIsTooLargeException if the number of crossoverPoints is too large for the actual chromosomes
     */
    private ChromosomePair mate(final AbstractListChromosome first,
                                final AbstractListChromosome second)
        throws DimensionMismatchException, NumberIsTooLargeException {

        final int length = first.getLength();
        if (length != second.getLength()) {
            throw new DimensionMismatchException(second.getLength(), length);
        }
        if (crossoverPoints >= length) {
            throw new NumberIsTooLargeException(crossoverPoints, length, false);
        }

        // array representations of the parents
        final List parent1Rep = first.getRepresentation();
        final List parent2Rep = second.getRepresentation();
        // and of the children
        final List child1Rep = new ArrayList(length);
        final List child2Rep = new ArrayList(length);

        final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();

        List c1 = child1Rep;
        List c2 = child2Rep;

        int remainingPoints = crossoverPoints;
        int lastIndex = 0;
        for (int i = 0; i < crossoverPoints; i++, remainingPoints--) {
            // select the next crossover point at random
            final int crossoverIndex = 1 + lastIndex + random.nextInt(length - lastIndex - remainingPoints);

            // copy the current segment
            for (int j = lastIndex; j < crossoverIndex; j++) {
                c1.add(parent1Rep.get(j));
                c2.add(parent2Rep.get(j));
            }

            // swap the children for the next segment
            List tmp = c1;
            c1 = c2;
            c2 = tmp;

            lastIndex = crossoverIndex;
        }

        // copy the last segment
        for (int j = lastIndex; j < length; j++) {
            c1.add(parent1Rep.get(j));
            c2.add(parent2Rep.get(j));
        }

        return new ChromosomePair(first.newFixedLengthChromosome(child1Rep),
                                  second.newFixedLengthChromosome(child2Rep));
    }
}