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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.mahout.math.jet.random;
import org.apache.mahout.common.RandomUtils;
import org.apache.mahout.math.MahoutTestCase;
import org.junit.Test;
import java.util.Arrays;
public final class ExponentialTest extends MahoutTestCase {
@Test
public void consistency() throws Exception {
Exponential dist = new Exponential(1, RandomUtils.getRandom());
// deciles computed using R
double[] breaks = {0.1053605, 0.2231436, 0.3566749, 0.5108256, 0.6931472, 0.9162907, 1.2039728, 1.6094379, 2.3025851};
for (double lambda : new double[]{0.01, 0.1, 1, 2, 5, 100}) {
dist.setState(lambda);
DistributionChecks.checkDistribution(dist, breaks, 0, 1 / lambda, 10000);
}
}
@Test
public void testCdf() {
Exponential dist = new Exponential(5.0, RandomUtils.getRandom());
for (int i = 0; i < 1000; i++) {
double x = i / 50.0;
assertEquals(1 - Math.exp(-x * 5.0), dist.cdf(x), 1.0e-9);
}
}
@Test
public void testPdf() {
checkPdf(new Exponential(13.0, null), 13.0);
}
private static void checkPdf(Exponential dist, double lambda) {
assertEquals(0, dist.pdf(-1), 0);
double sum = 0;
double dx = 0.001 / lambda;
for (double x = 0; x < 20/lambda;x+=dx) {
sum += x * dist.pdf(x) * dx;
assertEquals(Math.exp(-x * lambda) * lambda, dist.pdf(x), 1.0e-9);
}
assertEquals(1 / lambda, sum, 1.0e-6 / lambda);
}
@Test
public void testSetState() {
Exponential dist = new Exponential(13.0, null);
for (double lambda = 0.1; lambda < 1000; lambda *= 1.3) {
dist.setState(lambda);
checkPdf(dist, lambda);
}
}
@Test
public void testNextDouble() throws Exception {
double[] x = {
-0.01, 0.1053605, 0.2231436, 0.3566749, 0.5108256, 0.6931472, 0.9162907, 1.2039728, 1.6094379, 2.3025851
};
Exponential dist = new Exponential(1, RandomUtils.getRandom());
for (double lambda : new double[]{13.0, 0.02, 1.6}) {
dist.setState(lambda);
checkEmpiricalDistribution(dist, 10000, lambda);
DistributionChecks.checkDistribution(dist, x, 0, 1 / lambda, 10000);
}
}
private static void checkEmpiricalDistribution(Exponential dist, int n, double lambda) {
double[] x = new double[n];
for (int i = 0; i < n; i++) {
x[i] = dist.nextDouble();
}
Arrays.sort(x);
for (int i = 0; i < n; i++) {
double cumulative = (double) i / (n - 1);
assertEquals(String.format("lambda = %.3f", lambda), cumulative, dist.cdf(x[i]), 0.02);
}
}
@Test
public void testToString() {
assertEquals("org.apache.mahout.math.jet.random.Exponential(3.1000)", new Exponential(3.1, null).toString());
assertEquals("org.apache.mahout.math.jet.random.Exponential(3.1000)", new Exponential(3.1, null).toString());
}
}