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Java example source code file (UniformRealDistributionTest.java)

This example Java source code file (UniformRealDistributionTest.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

override, realdistributionabstracttest, test, uniformrealdistribution, uniformrealdistributiontest

The UniformRealDistributionTest.java Java example source code

/*
 * 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);
    }
}

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