/*
* 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.math.optimization;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
import static org.junit.Assert.fail;
import java.io.Serializable;
import org.apache.commons.math.FunctionEvaluationException;
import org.apache.commons.math.analysis.DifferentiableMultivariateVectorialFunction;
import org.apache.commons.math.analysis.MultivariateMatrixFunction;
import org.apache.commons.math.linear.BlockRealMatrix;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.optimization.general.GaussNewtonOptimizer;
import org.apache.commons.math.random.GaussianRandomGenerator;
import org.apache.commons.math.random.JDKRandomGenerator;
import org.apache.commons.math.random.RandomVectorGenerator;
import org.apache.commons.math.random.UncorrelatedRandomVectorGenerator;
import org.junit.Test;
/**
* <p>Some of the unit tests are re-implementations of the MINPACK <a
* href="http://www.netlib.org/minpack/ex/file17">file17</a> and <a
* href="http://www.netlib.org/minpack/ex/file22">file22</a> test files.
* The redistribution policy for MINPACK is available <a
* href="http://www.netlib.org/minpack/disclaimer">here</a>, for
* convenience, it is reproduced below.</p>
* <table border="0" width="80%" cellpadding="10" align="center" bgcolor="#E0E0E0">
* <tr><td>
* Minpack Copyright Notice (1999) University of Chicago.
* All rights reserved
* </td></tr>
* <tr><td>
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* <ol>
* <li>Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.</li>
* <li>Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.</li>
* <li>The end-user documentation included with the redistribution, if any,
* must include the following acknowledgment:
* <code>This product includes software developed by the University of
* Chicago, as Operator of Argonne National Laboratory.</code>
* Alternately, this acknowledgment may appear in the software itself,
* if and wherever such third-party acknowledgments normally appear.</li>
* <li><strong>WARRANTY DISCLAIMER. THE SOFTWARE IS SUPPLIED "AS IS"
* WITHOUT WARRANTY OF ANY KIND. THE COPYRIGHT HOLDER, THE
* UNITED STATES, THE UNITED STATES DEPARTMENT OF ENERGY, AND
* THEIR EMPLOYEES: (1) DISCLAIM ANY WARRANTIES, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO ANY IMPLIED WARRANTIES
* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE
* OR NON-INFRINGEMENT, (2) DO NOT ASSUME ANY LEGAL LIABILITY
* OR RESPONSIBILITY FOR THE ACCURACY, COMPLETENESS, OR
* USEFULNESS OF THE SOFTWARE, (3) DO NOT REPRESENT THAT USE OF
* THE SOFTWARE WOULD NOT INFRINGE PRIVATELY OWNED RIGHTS, (4)
* DO NOT WARRANT THAT THE SOFTWARE WILL FUNCTION
* UNINTERRUPTED, THAT IT IS ERROR-FREE OR THAT ANY ERRORS WILL
* BE CORRECTED.</strong></li>
* <li><strong>LIMITATION OF LIABILITY. IN NO EVENT WILL THE COPYRIGHT
* HOLDER, THE UNITED STATES, THE UNITED STATES DEPARTMENT OF
* ENERGY, OR THEIR EMPLOYEES: BE LIABLE FOR ANY INDIRECT,
* INCIDENTAL, CONSEQUENTIAL, SPECIAL OR PUNITIVE DAMAGES OF
* ANY KIND OR NATURE, INCLUDING BUT NOT LIMITED TO LOSS OF
* PROFITS OR LOSS OF DATA, FOR ANY REASON WHATSOEVER, WHETHER
* SUCH LIABILITY IS ASSERTED ON THE BASIS OF CONTRACT, TORT
* (INCLUDING NEGLIGENCE OR STRICT LIABILITY), OR OTHERWISE,
* EVEN IF ANY OF SAID PARTIES HAS BEEN WARNED OF THE
* POSSIBILITY OF SUCH LOSS OR DAMAGES.</strong></li>
* <ol></td></tr>
* </table>
* @author Argonne National Laboratory. MINPACK project. March 1980 (original fortran minpack tests)
* @author Burton S. Garbow (original fortran minpack tests)
* @author Kenneth E. Hillstrom (original fortran minpack tests)
* @author Jorge J. More (original fortran minpack tests)
* @author Luc Maisonobe (non-minpack tests and minpack tests Java translation)
*/
public class MultiStartDifferentiableMultivariateVectorialOptimizerTest {
@Test
public void testTrivial() throws FunctionEvaluationException, OptimizationException {
LinearProblem problem =
new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
new GaussNewtonOptimizer(true);
JDKRandomGenerator g = new JDKRandomGenerator();
g.setSeed(16069223052l);
RandomVectorGenerator generator =
new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
new MultiStartDifferentiableMultivariateVectorialOptimizer(underlyingOptimizer,
10, generator);
optimizer.setMaxIterations(100);
optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6));
// no optima before first optimization attempt
try {
optimizer.getOptima();
fail("an exception should have been thrown");
} catch (IllegalStateException ise) {
// expected
}
VectorialPointValuePair optimum =
optimizer.optimize(problem, problem.target, new double[] { 1 }, new double[] { 0 });
assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
assertEquals(3.0, optimum.getValue()[0], 1.0e-10);
VectorialPointValuePair[] optima = optimizer.getOptima();
assertEquals(10, optima.length);
for (int i = 0; i < optima.length; ++i) {
assertEquals(1.5, optima[i].getPoint()[0], 1.0e-10);
assertEquals(3.0, optima[i].getValue()[0], 1.0e-10);
}
assertTrue(optimizer.getEvaluations() > 20);
assertTrue(optimizer.getEvaluations() < 50);
assertTrue(optimizer.getIterations() > 20);
assertTrue(optimizer.getIterations() < 50);
assertTrue(optimizer.getJacobianEvaluations() > 20);
assertTrue(optimizer.getJacobianEvaluations() < 50);
assertEquals(100, optimizer.getMaxIterations());
}
@Test(expected = OptimizationException.class)
public void testNoOptimum() throws FunctionEvaluationException, OptimizationException {
DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
new GaussNewtonOptimizer(true);
JDKRandomGenerator g = new JDKRandomGenerator();
g.setSeed(12373523445l);
RandomVectorGenerator generator =
new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
new MultiStartDifferentiableMultivariateVectorialOptimizer(underlyingOptimizer,
10, generator);
optimizer.setMaxIterations(100);
optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6));
optimizer.optimize(new DifferentiableMultivariateVectorialFunction() {
public MultivariateMatrixFunction jacobian() {
return null;
}
public double[] value(double[] point) throws FunctionEvaluationException {
throw new FunctionEvaluationException(point[0]);
}
}, new double[] { 2 }, new double[] { 1 }, new double[] { 0 });
}
private static class LinearProblem implements DifferentiableMultivariateVectorialFunction, Serializable {
private static final long serialVersionUID = -8804268799379350190L;
final RealMatrix factors;
final double[] target;
public LinearProblem(double[][] factors, double[] target) {
this.factors = new BlockRealMatrix(factors);
this.target = target;
}
public double[] value(double[] variables) {
return factors.operate(variables);
}
public MultivariateMatrixFunction jacobian() {
return new MultivariateMatrixFunction() {
private static final long serialVersionUID = -8387467946663627585L;
public double[][] value(double[] point) {
return factors.getData();
}
};
}
}
}