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Java example source code file (MultiStartUnivariateOptimizerTest.java)

This example Java source code file (MultiStartUnivariateOptimizerTest.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

brentoptimizer, jdkrandomgenerator, localexception, maxeval, multistartunivariateoptimizer, multistartunivariateoptimizertest, runtimeexception, searchinterval, sin, test, univariatefunction, univariateobjectivefunction, univariateoptimizer, univariatepointvaluepair

The MultiStartUnivariateOptimizerTest.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.optim.univariate;

import org.apache.commons.math3.analysis.QuinticFunction;
import org.apache.commons.math3.analysis.UnivariateFunction;
import org.apache.commons.math3.analysis.function.Sin;
import org.apache.commons.math3.optim.nonlinear.scalar.GoalType;
import org.apache.commons.math3.optim.MaxEval;
import org.apache.commons.math3.random.JDKRandomGenerator;
import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.exception.MathIllegalStateException;
import org.junit.Assert;
import org.junit.Test;

public class MultiStartUnivariateOptimizerTest {
    @Test(expected=MathIllegalStateException.class)
    public void testMissingMaxEval() {
        UnivariateOptimizer underlying = new BrentOptimizer(1e-10, 1e-14);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(44428400075l);
        MultiStartUnivariateOptimizer optimizer = new MultiStartUnivariateOptimizer(underlying, 10, g);
        optimizer.optimize(new UnivariateObjectiveFunction(new Sin()),
                           GoalType.MINIMIZE,
                           new SearchInterval(-1, 1));
    }
    @Test(expected=MathIllegalStateException.class)
    public void testMissingSearchInterval() {
        UnivariateOptimizer underlying = new BrentOptimizer(1e-10, 1e-14);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(44428400075l);
        MultiStartUnivariateOptimizer optimizer = new MultiStartUnivariateOptimizer(underlying, 10, g);
        optimizer.optimize(new MaxEval(300),
                           new UnivariateObjectiveFunction(new Sin()),
                           GoalType.MINIMIZE);
    }

    @Test
    public void testSinMin() {
        UnivariateFunction f = new Sin();
        UnivariateOptimizer underlying = new BrentOptimizer(1e-10, 1e-14);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(44428400075l);
        MultiStartUnivariateOptimizer optimizer = new MultiStartUnivariateOptimizer(underlying, 10, g);
        optimizer.optimize(new MaxEval(300),
                           new UnivariateObjectiveFunction(f),
                           GoalType.MINIMIZE,
                           new SearchInterval(-100.0, 100.0));
        UnivariatePointValuePair[] optima = optimizer.getOptima();
        for (int i = 1; i < optima.length; ++i) {
            double d = (optima[i].getPoint() - optima[i-1].getPoint()) / (2 * FastMath.PI);
            Assert.assertTrue(FastMath.abs(d - FastMath.rint(d)) < 1.0e-8);
            Assert.assertEquals(-1.0, f.value(optima[i].getPoint()), 1.0e-10);
            Assert.assertEquals(f.value(optima[i].getPoint()), optima[i].getValue(), 1.0e-10);
        }
        Assert.assertTrue(optimizer.getEvaluations() > 200);
        Assert.assertTrue(optimizer.getEvaluations() < 300);
    }

    @Test
    public void testQuinticMin() {
        // The quintic function has zeros at 0, +-0.5 and +-1.
        // The function has extrema (first derivative is zero) at 0.27195613 and 0.82221643,
        UnivariateFunction f = new QuinticFunction();
        UnivariateOptimizer underlying = new BrentOptimizer(1e-9, 1e-14);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(4312000053L);
        MultiStartUnivariateOptimizer optimizer = new MultiStartUnivariateOptimizer(underlying, 5, g);

        UnivariatePointValuePair optimum
            = optimizer.optimize(new MaxEval(300),
                                 new UnivariateObjectiveFunction(f),
                                 GoalType.MINIMIZE,
                                 new SearchInterval(-0.3, -0.2));
        Assert.assertEquals(-0.27195613, optimum.getPoint(), 1e-9);
        Assert.assertEquals(-0.0443342695, optimum.getValue(), 1e-9);

        UnivariatePointValuePair[] optima = optimizer.getOptima();
        for (int i = 0; i < optima.length; ++i) {
            Assert.assertEquals(f.value(optima[i].getPoint()), optima[i].getValue(), 1e-9);
        }
        Assert.assertTrue(optimizer.getEvaluations() >= 50);
        Assert.assertTrue(optimizer.getEvaluations() <= 100);
    }

    @Test
    public void testBadFunction() {
        UnivariateFunction f = new UnivariateFunction() {
                public double value(double x) {
                    if (x < 0) {
                        throw new LocalException();
                    }
                    return 0;
                }
            };
        UnivariateOptimizer underlying = new BrentOptimizer(1e-9, 1e-14);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(4312000053L);
        MultiStartUnivariateOptimizer optimizer = new MultiStartUnivariateOptimizer(underlying, 5, g);

        try {
            optimizer.optimize(new MaxEval(300),
                               new UnivariateObjectiveFunction(f),
                               GoalType.MINIMIZE,
                               new SearchInterval(-0.3, -0.2));
            Assert.fail();
        } catch (LocalException e) {
            // Expected.
        }

        // Ensure that the exception was thrown because no optimum was found.
        Assert.assertTrue(optimizer.getOptima()[0] == null);
    }

    private static class LocalException extends RuntimeException {
        private static final long serialVersionUID = 1194682757034350629L;
    }

}

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