/*
 * Java Genetic Algorithm Library (jenetics-7.2.0).
 * Copyright (c) 2007-2023 Franz Wilhelmstötter
 *
 * Licensed 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.
 *
 * Author:
 *    Franz Wilhelmstötter (franz.wilhelmstoetter@gmail.com)
 */
package io.jenetics;

import static java.lang.String.format;
import static java.util.Objects.requireNonNull;

import java.util.Comparator;
import java.util.random.RandomGenerator;
import java.util.stream.Stream;

import io.jenetics.util.ISeq;
import io.jenetics.util.MSeq;
import io.jenetics.util.RandomRegistry;
import io.jenetics.util.Seq;

/**
 * In tournament selection the best individual from a random sample of <i>s</i>
 * individuals is chosen from the population <i>P<sub>g</sub></i>. The samples
 * are drawn with replacement. An individual will win a tournament only if its
 * fitness is greater than the fitness of the other <i>s-1</i>  competitors.
 * Note that the worst individual never survives, and the best individual wins
 * in all the tournaments it participates. The selection pressure can be varied
 * by changing the tournament size <i>s</i> . For large values of <i>s</i>, weak
 * individuals have less chance being selected.
 *
 * @see <a href="http://en.wikipedia.org/wiki/Tournament_selection">Tournament selection</a>
 *
 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
 * @since 1.0
 * @version 6.0
 */
public class TournamentSelector<
        G extends Gene<?, G>,
        C extends Comparable<? super C>
>
        implements Selector<G, C>
{

        private final Comparator<? super Phenotype<G, C>> _comparator;
        private final int _sampleSize;

        /**
         * Create a tournament selector with the give {@code comparator} and
         * sample size. The sample size must be greater than one.
         *
         * @since 6.0
         *
         * @param comparator the comparator use for comparing two individuals during
         *        a tournament
         * @param sampleSize the number of individuals involved in one tournament
         * @throws IllegalArgumentException if the sample size is smaller than two
         * @throws NullPointerException if the given {@code comparator} is
         *         {@code null}
         */
        public TournamentSelector(
                final Comparator<? super Phenotype<G, C>> comparator,
                final int sampleSize
        ) {
                _comparator = requireNonNull(comparator);
                if (sampleSize < 2) {
                        throw new IllegalArgumentException(
                                "Sample size must be greater than one, but was " + sampleSize
                        );
                }
                _sampleSize = sampleSize;
        }

        /**
         * Create a tournament selector with the give sample size. The sample size
         * must be greater than one.
         *
         * @param sampleSize the number of individuals involved in one tournament
         * @throws IllegalArgumentException if the sample size is smaller than two.
         */
        public TournamentSelector(final int sampleSize) {
                this(Phenotype::compareTo, sampleSize);
        }

        /**
         * Create a tournament selector with sample size two.
         */
        public TournamentSelector() {
                this(Phenotype::compareTo,2);
        }

        /**
         * Return the sample size of the tournament selector.
         *
         * @since 5.0
         *
         * @return the sample size of the tournament selector
         */
        public int sampleSize() {
                return _sampleSize;
        }

        @Override
        public ISeq<Phenotype<G, C>> select(
                final Seq<Phenotype<G, C>> population,
                final int count,
                final Optimize opt
        ) {
                requireNonNull(population, "Population");
                requireNonNull(opt, "Optimization");
                if (count < 0) {
                        throw new IllegalArgumentException(format(
                                "Selection count must be greater or equal then zero, but was %s",
                                count
                        ));
                }

                final var random = RandomRegistry.random();
                return population.isEmpty()
                        ? ISeq.empty()
                        : MSeq.<Phenotype<G, C>>ofLength(count)
                                .fill(() -> select(population, opt, random))
                                .toISeq();
        }

        private Phenotype<G, C> select(
                final Seq<Phenotype<G, C>> population,
                final Optimize opt,
                final RandomGenerator random
        ) {
                final int N = population.size();

                assert _sampleSize >= 2;
                assert N >= 1;

                final Comparator<? super Phenotype<G, C>> cmp = opt == Optimize.MAXIMUM
                        ? _comparator
                        : _comparator.reversed();

                return Stream.generate(() -> population.get(random.nextInt(N)))
                        .limit(_sampleSize)
                        .max(cmp)
                        .orElseThrow(AssertionError::new);
        }

        @Override
        public String toString() {
                return format("%s[s=%d]", getClass().getSimpleName(), _sampleSize);
        }

}