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Java example source code file (MultiStartUnivariateOptimizerTest.java)
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; } } Other Java examples (source code examples)Here is a short list of links related to this Java MultiStartUnivariateOptimizerTest.java source code file: |
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