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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.statistics.distribution;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
/**
* Test cases for GumbelDistribution.
*/
public class GumbelDistributionTest extends ContinuousDistributionAbstractTest {
//-------------- Implementations for abstract methods ----------------------
@Override
public GumbelDistribution makeDistribution() {
return new GumbelDistribution(0.5, 2);
}
@Override
public double[] makeCumulativeTestPoints() {
return new double[] {
-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5
};
}
@Override
public double[] makeDensityTestValues() {
return new double[] {
1.258262e-06, 3.594689e-04, 9.115766e-03, 5.321100e-02, 1.274352e-01, 1.777864e-01,
1.787177e-01, 1.472662e-01, 1.075659e-01, 7.302736e-02, 4.742782e-02
};
}
@Override
public double[] makeCumulativeTestValues() {
return new double[] {
1.608760e-07, 7.577548e-05, 3.168165e-03, 3.049041e-02, 1.203923e-01, 2.769203e-01,
4.589561e-01, 6.235249e-01, 7.508835e-01, 8.404869e-01, 8.999652e-01
};
}
//-------------------- Additional test cases -------------------------------
@Test
public void testInverseCumulativeProbabilityExtremes() {
setInverseCumulativeTestPoints(new double[] {0.0, 1.0});
setInverseCumulativeTestValues(new double[] {Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY});
verifyInverseCumulativeProbabilities();
}
@Test
public void testParameterAccessors() {
final GumbelDistribution d = makeDistribution();
Assertions.assertEquals(0.5, d.getLocation());
Assertions.assertEquals(2, d.getScale());
}
@Test
public void testConstructorPrecondition1() {
Assertions.assertThrows(IllegalArgumentException.class, () -> new GumbelDistribution(10, -0.1));
}
@Test
public void testMoments() {
final double tol = 1e-9;
GumbelDistribution dist;
dist = new GumbelDistribution(10, 0.5);
Assertions.assertEquals(10 + (Math.PI / (2 * Math.E)) * 0.5, dist.getMean(), tol);
Assertions.assertEquals((Math.PI * Math.PI / 6) * 0.5 * 0.5, dist.getVariance(), tol);
dist = new GumbelDistribution(30, 0.3);
Assertions.assertEquals(30 + (Math.PI / (2 * Math.E)) * 0.3, dist.getMean(), tol);
Assertions.assertEquals((Math.PI * Math.PI / 6) * 0.3 * 0.3, dist.getVariance(), tol);
}
@Test
public void testSupport() {
final GumbelDistribution d = makeDistribution();
Assertions.assertEquals(Double.NEGATIVE_INFINITY, d.getSupportLowerBound());
Assertions.assertEquals(Double.POSITIVE_INFINITY, d.getSupportUpperBound());
Assertions.assertTrue(d.isSupportConnected());
}
}