/*
* Java Genetic Algorithm Library (@__identifier__@).
* Copyright (c) @__year__@ 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@gmx.at)
*/
package org.jenetics;
import static org.jenetics.stat.StatisticsAssert.assertUniformDistribution;
import static org.jenetics.util.RandomRegistry.using;
import static org.testng.Assert.assertEquals;
import java.util.Random;
import java.util.stream.IntStream;
import org.testng.Assert;
import org.testng.annotations.Test;
import org.jenetics.stat.Histogram;
import org.jenetics.util.Factory;
/**
* @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
*/
public class LongGeneTest extends NumericGeneTester<Long, LongGene> {
private final Factory<LongGene> _factory = LongGene.of(0, Long.MAX_VALUE);
@Override protected Factory<LongGene> factory() {
return _factory;
}
@Test(invocationCount = 20, successPercentage = 95)
public void newInstanceDistribution() {
final Long min = 0L;
final Long max = (long)Integer.MAX_VALUE;
final Histogram<Long> histogram = Histogram.ofLong(min, max, 10);
using(new Random(12345), r ->
IntStream.range(0, 200_000)
.mapToObj(i -> LongGene.of(min, max).getAllele())
.forEach(histogram::accept)
);
assertUniformDistribution(histogram);
}
@Test
public void mean() {
final long min = -Integer.MAX_VALUE;
final long max = Integer.MAX_VALUE;
final LongGene template = LongGene.of(min, max);
for (int i = 1; i < 500; ++i) {
final LongGene a = template.newInstance(i - 50L);
final LongGene b = template.newInstance((i - 100L) *3);
final LongGene c = a.mean(b);
assertEquals(a.getMin().longValue(), min);
assertEquals(a.getMax().longValue(), max);
assertEquals(b.getMin().longValue(), min);
assertEquals(b.getMax().longValue(), max);
assertEquals(c.getMin().longValue(), min);
assertEquals(c.getMax().longValue(), max);
assertEquals(c.getAllele().longValue(), ((i - 50) + ((i - 100)*3))/2);
}
}
@Test
public void createNumber() {
LongGene gene = LongGene.of(1, 0, 12);
LongGene g2 = gene.newInstance(5L);
assertEquals(g2.getAllele().longValue(), 5);
assertEquals(g2.getMin().longValue(), 0);
assertEquals(g2.getMax().longValue(), 12);
}
@Test
public void createInvalidNumber() {
final LongGene gene = LongGene.of(0, 1, 2);
Assert.assertFalse(gene.isValid());
}
@Test
public void set() {
LongGene gene = new LongGene(5L, 0L, 10L);
Assert.assertEquals(gene.getAllele().longValue(), 5L);
Assert.assertEquals(gene.getMin().longValue(), 0L);
Assert.assertEquals(gene.getMax().longValue(), 10L);
}
}