1   /*
2    * Licensed to the Apache Software Foundation (ASF) under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * The ASF licenses this file to You under the Apache License, Version 2.0
6    * (the "License"); you may not use this file except in compliance with
7    * the License.  You may obtain a copy of the License at
8    *
9    *      http://www.apache.org/licenses/LICENSE-2.0
10   *
11   * Unless required by applicable law or agreed to in writing, software
12   * distributed under the License is distributed on an "AS IS" BASIS,
13   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14   * See the License for the specific language governing permissions and
15   * limitations under the License.
16   */
17  
18  package org.apache.commons.math.optimization;
19  
20  import static org.junit.Assert.assertEquals;
21  import static org.junit.Assert.assertTrue;
22  
23  import org.apache.commons.math.ConvergenceException;
24  import org.apache.commons.math.FunctionEvaluationException;
25  import org.apache.commons.math.analysis.MultivariateRealFunction;
26  import org.apache.commons.math.optimization.direct.NelderMead;
27  import org.apache.commons.math.random.GaussianRandomGenerator;
28  import org.apache.commons.math.random.JDKRandomGenerator;
29  import org.apache.commons.math.random.RandomVectorGenerator;
30  import org.apache.commons.math.random.UncorrelatedRandomVectorGenerator;
31  import org.junit.Test;
32  
33  public class MultiStartMultivariateRealOptimizerTest {
34  
35    @Test
36    public void testRosenbrock()
37      throws FunctionEvaluationException, ConvergenceException {
38  
39      Rosenbrock rosenbrock = new Rosenbrock();
40      NelderMead underlying = new NelderMead();
41      underlying.setStartConfiguration(new double[][] {
42                                           { -1.2,  1.0 }, { 0.9, 1.2 } , {  3.5, -2.3 }
43                                       });
44      JDKRandomGenerator g = new JDKRandomGenerator();
45      g.setSeed(16069223052l);
46      RandomVectorGenerator generator =
47          new UncorrelatedRandomVectorGenerator(2, new GaussianRandomGenerator(g));
48      MultiStartMultivariateRealOptimizer optimizer =
49          new MultiStartMultivariateRealOptimizer(underlying, 10, generator);
50      optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1, 1.0e-3));
51      optimizer.setMaxIterations(100);
52      RealPointValuePair optimum =
53          optimizer.optimize(rosenbrock, GoalType.MINIMIZE, new double[] { -1.2, 1.0 });
54  
55      assertEquals(rosenbrock.getCount(), optimizer.getEvaluations());
56      assertTrue(optimizer.getEvaluations() > 20);
57      assertTrue(optimizer.getEvaluations() < 250);
58      assertTrue(optimum.getValue() < 8.0e-4);
59  
60    }
61  
62    private static class Rosenbrock implements MultivariateRealFunction {
63  
64        private int count;
65  
66        public Rosenbrock() {
67            count = 0;
68        }
69  
70        public double value(double[] x) throws FunctionEvaluationException {
71            ++count;
72            double a = x[1] - x[0] * x[0];
73            double b = 1.0 - x[0];
74            return 100 * a * a + b * b;
75        }
76  
77        public int getCount() {
78            return count;
79        }
80  
81    }
82  
83  }