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/*
 * Java Genetic Algorithm Library (jenetics-3.4.0).
 * Copyright (c) 2007-2016 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 ([email protected])
 */
package org.jenetics;

import static org.jenetics.internal.math.random.nextLong;
import static org.jenetics.util.RandomRegistry.getRandom;

import java.io.Serializable;
import java.util.Random;

import javax.xml.bind.annotation.XmlAccessType;
import javax.xml.bind.annotation.XmlAccessorType;
import javax.xml.bind.annotation.XmlAttribute;
import javax.xml.bind.annotation.XmlRootElement;
import javax.xml.bind.annotation.XmlType;
import javax.xml.bind.annotation.XmlValue;
import javax.xml.bind.annotation.adapters.XmlAdapter;
import javax.xml.bind.annotation.adapters.XmlJavaTypeAdapter;

import org.jenetics.util.ISeq;
import org.jenetics.util.LongRange;
import org.jenetics.util.MSeq;
import org.jenetics.util.Mean;

/**
 * NumericGene implementation which holds a 64 bit integer number.
 *
 * 

This is a * value-based class; use of identity-sensitive operations (including * reference equality ({@code ==}), identity hash code, or synchronization) on * instances of {@code LongGene} may have unpredictable results and should * be avoided. * * @author Franz Wilhelmstötter * @since 1.6 * @version 3.2 */ @XmlJavaTypeAdapter(LongGene.Model.Adapter.class) public final class LongGene extends AbstractNumericGene implements NumericGene, Mean, Comparable, Serializable { private static final long serialVersionUID = 1L; /** * Create a new random {@code LongGene} with the given value and the * given range. If the {@code value} isn't within the interval [min, max], * no exception is thrown. In this case the method * {@link LongGene#isValid()} returns {@code false}. * * @param value the value of the gene. * @param min the minimal valid value of this gene (inclusively). * @param max the maximal valid value of this gene (inclusively). * @throws NullPointerException if one of the arguments is {@code null}. */ LongGene(final Long value, final Long min, final Long max) { super(value, min, max); } @Override public int compareTo(final LongGene other) { return _value.compareTo(other._value); } /** * Create a new random {@code LongGene} with the given value and the * given range. If the {@code value} isn't within the interval [min, max], * no exception is thrown. In this case the method * {@link LongGene#isValid()} returns {@code false}. * * @param value the value of the gene. * @param min the minimal valid value of this gene (inclusively). * @param max the maximal valid value of this gene (inclusively). * @return a new {@code LongGene} with the given parameters. */ public static LongGene of(final long value, final long min, final long max) { return new LongGene(value, min, max); } /** * Create a new random {@code LongGene} with the given value and the * given range. If the {@code value} isn't within the interval [min, max], * no exception is thrown. In this case the method * {@link LongGene#isValid()} returns {@code false}. * * @since 3.2 * * @param value the value of the gene. * @param range the long range to use * @return a new random {@code LongGene} * @throws NullPointerException if the given {@code range} is {@code null}. */ public static LongGene of(final long value, final LongRange range) { return new LongGene(value, range.getMin(), range.getMax()); } /** * Create a new random {@code LongGene}. It is guaranteed that the value of * the {@code LongGene} lies in the interval [min, max]. * * @param min the minimal valid value of this gene (inclusively). * @param max the maximal valid value of this gene (inclusively). * @return a new {@code LongGene} with the given parameters. */ public static LongGene of(final long min, final long max) { return of(nextLong(getRandom(), min, max), min, max); } /** * Create a new random {@code LongGene}. It is guaranteed that the value of * the {@code LongGene} lies in the interval [min, max]. * * @since 3.2 * * @param range the long range to use * @return a new random {@code LongGene} * @throws NullPointerException if the given {@code range} is {@code null}. */ public static LongGene of(final LongRange range) { return of(nextLong(getRandom(), range.getMin(), range.getMax()), range); } static ISeq seq( final Long minimum, final Long maximum, final int length ) { final long min = minimum; final long max = maximum; final Random r = getRandom(); return MSeq.ofLength(length) .fill(() -> new LongGene(nextLong(r, min, max), minimum, maximum)) .toISeq(); } @Override public LongGene newInstance(final Number number) { return new LongGene(number.longValue(), _min, _max); } @Override public LongGene newInstance() { return new LongGene( nextLong(getRandom(), _min, _max), _min, _max ); } @Override public LongGene mean(final LongGene that) { return new LongGene(_value + (that._value - _value)/2, _min, _max); } /* ************************************************************************* * JAXB object serialization * ************************************************************************/ @XmlRootElement(name = "long-gene") @XmlType(name = "org.jenetics.LongGene") @XmlAccessorType(XmlAccessType.FIELD) final static class Model { @XmlAttribute(name = "min", required = true) public long min; @XmlAttribute(name = "max", required = true) public long max; @XmlValue public long value; public final static class Adapter extends XmlAdapter { @Override public Model marshal(final LongGene value) { final Model m = new Model(); m.min = value.getMin(); m.max = value.getMax(); m.value = value.getAllele(); return m; } @Override public LongGene unmarshal(final Model m) { return LongGene.of(m.value, m.min, m.max); } } } }





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