commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/optim/univariate/MultiStartUnivariateOptimizerTest.java

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 * 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
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 *      http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.commons.math4.legacy.optim.univariate;

import org.apache.commons.math4.legacy.analysis.QuinticFunction;
import org.apache.commons.math4.legacy.analysis.UnivariateFunction;
import org.apache.commons.math4.legacy.analysis.function.Sin;
import org.apache.commons.math4.legacy.exception.MathIllegalStateException;
import org.apache.commons.math4.legacy.optim.MaxEval;
import org.apache.commons.math4.legacy.optim.nonlinear.scalar.GoalType;
import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.simple.RandomSource;
import org.apache.commons.math4.core.jdkmath.JdkMath;
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);
        UniformRandomProvider g = RandomSource.TWO_CMRES.create(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);
        UniformRandomProvider g = RandomSource.TWO_CMRES.create(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);
        UniformRandomProvider g = RandomSource.TWO_CMRES.create(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 * JdkMath.PI);
            Assert.assertTrue(JdkMath.abs(d - JdkMath.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() {
        UnivariateFunction f = new QuinticFunction();
        UnivariateOptimizer underlying = new BrentOptimizer(1e-9, 1e-14);
        UniformRandomProvider g = RandomSource.TWO_CMRES.create(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(-0.2719561295, 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() {
                @Override
                public double value(double x) {
                    if (x < 0) {
                        throw new LocalException();
                    }
                    return 0;
                }
            };
        UnivariateOptimizer underlying = new BrentOptimizer(1e-9, 1e-14);
        UniformRandomProvider g = RandomSource.TWO_CMRES.create(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.assertNull(optimizer.getOptima()[0]);
    }

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