/*
 * 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.jenetics.example.image;

import static java.lang.String.format;

import java.util.Random;

import org.jenetics.Crossover;
import org.jenetics.Gene;
import org.jenetics.util.MSeq;
import org.jenetics.util.RandomRegistry;

/**
 * Perform Uniform Crossover [UX] on the specified genes. A fixed mixing ratio
 * is used to combine genes from the first and second parents, e.g. using a
 * ratio of 0.5 would result in approximately 50% of genes coming from each
 * parent. This is typically a poor method of crossover, but empirical evidence
 * suggests that it is more exploratory and results in a larger part of the
 * problem space being searched.
 * <p>
 * This crossover policy evaluates each gene of the parent genes by choosing a
 * uniform random number {@code p} in the range [0, 1]. If {@code p} <
 * {@code ratio}, the parent genes are swapped. This means with a ratio of 0.7,
 * 30% of the genes from the first parent and 70% from the second parent will
 * be selected for the first offspring (and vice versa for the second offspring).
 * <p>
 * The genes must have same lengths.
 *
 * @see <a href="http://en.wikipedia.org/wiki/Crossover_%28genetic_algorithm%29">
 *         Crossover techniques (Wikipedia)</a>
 * @see <a href="http://www.obitko.com/tutorials/genetic-algorithms/crossover-mutation.php">
 *         Crossover (Obitko.com)</a>
 * @see <a href="http://www.tomaszgwiazda.com/uniformX.htm">Uniform crossover</a>
 */
final class UniformCrossover<
	G extends Gene<?, G>,
	C extends Comparable<? super C>
>
	extends Crossover<G, C>
{

	/**
	* Constructs an alterer with a given recombination probability.
	*
	* @param probability the crossover probability.
	* @throws IllegalArgumentException if the {@code probability} is not in the
	*         valid range of {@code [0, 1]}.
	*/
	public UniformCrossover(final double probability) {
	super(probability);
	}

	@Override
	protected int crossover(final MSeq<G> that, final MSeq<G> other) {
		assert that.length() == other.length();

		int alteredGenes = 0;
		final Random random = RandomRegistry.getRandom();
		for (int i = 0; i < that.length(); ++i) {
			if (random.nextFloat() < getProbability()) {
				crossover(that, other, i);
				++alteredGenes;
			}
		}

		return alteredGenes;
	}

	// Package private for testing purpose.
	static <T> void crossover(
		final MSeq<T> that,
		final MSeq<T> other,
		final int index
	) {
		assert index >= 0 : format(
			"Crossover index must be within [0, %d) but was %d",
			that.length(), index
		);

		that.swap(index, index + 1, other, index);
	}

}