| /* |
| * 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.math3.distribution; |
| |
| import org.apache.commons.math3.exception.NumberIsTooLargeException; |
| import org.junit.Assert; |
| import org.junit.Test; |
| |
| /** |
| * Test cases for UniformRealDistribution. See class javadoc for |
| * {@link RealDistributionAbstractTest} for further details. |
| */ |
| public class UniformRealDistributionTest extends RealDistributionAbstractTest { |
| |
| // --- Override tolerance ------------------------------------------------- |
| |
| @Override |
| public void setUp() { |
| super.setUp(); |
| setTolerance(1e-4); |
| } |
| |
| //--- Implementations for abstract methods -------------------------------- |
| |
| /** Creates the default uniform real distribution instance to use in tests. */ |
| @Override |
| public UniformRealDistribution makeDistribution() { |
| return new UniformRealDistribution(-0.5, 1.25); |
| } |
| |
| /** Creates the default cumulative probability distribution test input values */ |
| @Override |
| public double[] makeCumulativeTestPoints() { |
| return new double[] {-0.5001, -0.5, -0.4999, -0.25, -0.0001, 0.0, |
| 0.0001, 0.25, 1.0, 1.2499, 1.25, 1.2501}; |
| } |
| |
| /** Creates the default cumulative probability density test expected values */ |
| @Override |
| public double[] makeCumulativeTestValues() { |
| return new double[] {0.0, 0.0, 0.0001, 0.25/1.75, 0.4999/1.75, |
| 0.5/1.75, 0.5001/1.75, 0.75/1.75, 1.5/1.75, |
| 1.7499/1.75, 1.0, 1.0}; |
| } |
| |
| /** Creates the default probability density test expected values */ |
| @Override |
| public double[] makeDensityTestValues() { |
| double d = 1 / 1.75; |
| return new double[] {0, d, d, d, d, d, d, d, d, d, d, 0}; |
| } |
| |
| //--- Additional test cases ----------------------------------------------- |
| |
| /** Test lower bound getter. */ |
| @Test |
| public void testGetLowerBound() { |
| UniformRealDistribution distribution = makeDistribution(); |
| Assert.assertEquals(-0.5, distribution.getSupportLowerBound(), 0); |
| } |
| |
| /** Test upper bound getter. */ |
| @Test |
| public void testGetUpperBound() { |
| UniformRealDistribution distribution = makeDistribution(); |
| Assert.assertEquals(1.25, distribution.getSupportUpperBound(), 0); |
| } |
| |
| /** Test pre-condition for equal lower/upper bound. */ |
| @Test(expected=NumberIsTooLargeException.class) |
| public void testPreconditions1() { |
| new UniformRealDistribution(0, 0); |
| } |
| |
| /** Test pre-condition for lower bound larger than upper bound. */ |
| @Test(expected=NumberIsTooLargeException.class) |
| public void testPreconditions2() { |
| new UniformRealDistribution(1, 0); |
| } |
| |
| /** Test mean/variance. */ |
| @Test |
| public void testMeanVariance() { |
| UniformRealDistribution dist; |
| |
| dist = new UniformRealDistribution(0, 1); |
| Assert.assertEquals(dist.getNumericalMean(), 0.5, 0); |
| Assert.assertEquals(dist.getNumericalVariance(), 1/12.0, 0); |
| |
| dist = new UniformRealDistribution(-1.5, 0.6); |
| Assert.assertEquals(dist.getNumericalMean(), -0.45, 0); |
| Assert.assertEquals(dist.getNumericalVariance(), 0.3675, 0); |
| |
| dist = new UniformRealDistribution(-0.5, 1.25); |
| Assert.assertEquals(dist.getNumericalMean(), 0.375, 0); |
| Assert.assertEquals(dist.getNumericalVariance(), 0.2552083333333333, 0); |
| } |
| |
| /** |
| * Check accuracy of analytical inverse CDF. Fails if a solver is used |
| * with the default accuracy. |
| */ |
| @Test |
| public void testInverseCumulativeDistribution() { |
| UniformRealDistribution dist = new UniformRealDistribution(0, 1e-9); |
| |
| Assert.assertEquals(2.5e-10, dist.inverseCumulativeProbability(0.25), 0); |
| } |
| } |