Author: luc
Date: Fri Jun 19 12:04:01 2009
New Revision: 786467
URL: http://svn.apache.org/viewvc?rev=786467&view=rev
Log:
added new tests
Added:
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartDifferentiableMultivariateVectorialOptimizerTest.java
(with props)
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizerTest.java
(with props)
Added:
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartDifferentiableMultivariateVectorialOptimizerTest.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartDifferentiableMultivariateVectorialOptimizerTest.java?rev=786467&view=auto
==============================================================================
---
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartDifferentiableMultivariateVectorialOptimizerTest.java
(added)
+++
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartDifferentiableMultivariateVectorialOptimizerTest.java
Fri Jun 19 12:04:01 2009
@@ -0,0 +1,192 @@
+/*
+ * 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();
+ }
+ };
+ }
+
+ }
+
+}
Propchange:
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartDifferentiableMultivariateVectorialOptimizerTest.java
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svn:keywords = Author Date Id Revision
Added:
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizerTest.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizerTest.java?rev=786467&view=auto
==============================================================================
---
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizerTest.java
(added)
+++
commons/proper/math/trunk/src/test/org/apache/commons/math/optimization/MultiStartMultivariateRealOptimizerTest.java
Fri Jun 19 12:04:01 2009
@@ -0,0 +1,83 @@
+/*
+ * 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 org.apache.commons.math.ConvergenceException;
+import org.apache.commons.math.FunctionEvaluationException;
+import org.apache.commons.math.analysis.MultivariateRealFunction;
+import org.apache.commons.math.optimization.direct.NelderMead;
+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;
+
+public class MultiStartMultivariateRealOptimizerTest {
+
+ @Test
+ public void testRosenbrock()
+ throws FunctionEvaluationException, ConvergenceException {
+
+ Rosenbrock rosenbrock = new Rosenbrock();
+ NelderMead underlying = new NelderMead();
+ underlying.setStartConfiguration(new double[][] {
+ { -1.2, 1.0 }, { 0.9, 1.2 } , {
3.5, -2.3 }
+ });
+ JDKRandomGenerator g = new JDKRandomGenerator();
+ g.setSeed(16069223052l);
+ RandomVectorGenerator generator =
+ new UncorrelatedRandomVectorGenerator(2, new
GaussianRandomGenerator(g));
+ MultiStartMultivariateRealOptimizer optimizer =
+ new MultiStartMultivariateRealOptimizer(underlying, 10, generator);
+ optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1, 1.0e-3));
+ optimizer.setMaxIterations(100);
+ RealPointValuePair optimum =
+ optimizer.optimize(rosenbrock, GoalType.MINIMIZE, new double[] { -1.2,
1.0 });
+
+ assertEquals(rosenbrock.getCount(), optimizer.getEvaluations());
+ assertTrue(optimizer.getEvaluations() > 20);
+ assertTrue(optimizer.getEvaluations() < 250);
+ assertTrue(optimum.getValue() < 8.0e-4);
+
+ }
+
+ private class Rosenbrock implements MultivariateRealFunction {
+
+ private int count;
+
+ public Rosenbrock() {
+ count = 0;
+ }
+
+ public double value(double[] x) throws FunctionEvaluationException {
+ ++count;
+ double a = x[1] - x[0] * x[0];
+ double b = 1.0 - x[0];
+ return 100 * a * a + b * b;
+ }
+
+ public int getCount() {
+ return count;
+ }
+
+ }
+
+}
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