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1   /*
2    * Licensed to the Hipparchus project 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 Hipparchus project 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    *      https://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  package org.hipparchus.optim.nonlinear.vector.constrained;
18  
19  import org.hipparchus.optim.OptimizationData;
20  import org.hipparchus.optim.nonlinear.scalar.ObjectiveFunction;
21  import org.junit.jupiter.api.Test;
22  
23  import static org.junit.jupiter.api.Assertions.assertEquals;
24  
25  class SQPOptimizerGMTest extends AbstractTestAbstractSQPOptimizerTest {
26  
27      protected ConstraintOptimizer buildOptimizer() {
28          return new SQPOptimizerGM();
29      }
30  
31      @Test
32      void testWithEqualityConstraintsOnly() {
33          final QuadraticFunction q = new QuadraticFunction(new double[][] { { 1.0, 0.0 }, { 0.0, 1.0 } },
34                  new double[] { 1.0, 0.0 },
35                  0.0);
36  
37          final LinearEqualityConstraint eqc = new LinearEqualityConstraint(new double[][] { { 1.0, 0.0 } },
38                  new double[] { 1.0 });
39  
40          final ConstraintOptimizer optimizer = buildOptimizer();
41          final OptimizationData[] data = new OptimizationData[] { new ObjectiveFunction(q), eqc };
42          final LagrangeSolution    solution  = optimizer.optimize(data);
43  
44          assertEquals(1.5, solution.getValue(), 1.e-4);
45      }
46  
47      @Test
48      void testWithInequalityConstraintsOnly() {
49          final QuadraticFunction q = new QuadraticFunction(new double[][] { { 1.0, 0.0 }, { 0.0, 1.0 } },
50                  new double[] { 1.0, 0.0 },
51                  0.0);
52  
53          final LinearInequalityConstraint eqc = new LinearInequalityConstraint(new double[][] { { 1.0, 0.0 } },
54                  new double[] { 1.0 });
55  
56          final ConstraintOptimizer optimizer = buildOptimizer();
57          final OptimizationData[] data = new OptimizationData[] { new ObjectiveFunction(q), eqc };
58          final LagrangeSolution    solution  = optimizer.optimize(data);
59  
60          assertEquals(1.5, solution.getValue(), 1.e-4);
61      }
62  
63  }