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 * 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
18 /*
19 * This is not the original file distributed by the Apache Software Foundation
20 * It has been modified by the Hipparchus project
21 */
22 package org.hipparchus.optim.nonlinear.scalar;
23
24 import org.hipparchus.analysis.MultivariateFunction;
25 import org.hipparchus.exception.MathIllegalStateException;
26 import org.hipparchus.optim.BaseMultivariateOptimizer;
27 import org.hipparchus.optim.ConvergenceChecker;
28 import org.hipparchus.optim.OptimizationData;
29 import org.hipparchus.optim.PointValuePair;
30
31 /**
32 * Base class for a multivariate scalar function optimizer.
33 *
34 */
35 public abstract class MultivariateOptimizer
36 extends BaseMultivariateOptimizer<PointValuePair> {
37 /** Objective function. */
38 private MultivariateFunction function;
39 /** Type of optimization. */
40 private GoalType goal;
41
42 /** Simple constructor.
43 * @param checker Convergence checker.
44 */
45 protected MultivariateOptimizer(ConvergenceChecker<PointValuePair> checker) {
46 super(checker);
47 }
48
49 /**
50 * {@inheritDoc}
51 *
52 * @param optData Optimization data. In addition to those documented in
53 * {@link BaseMultivariateOptimizer#parseOptimizationData(OptimizationData[])
54 * BaseMultivariateOptimizer}, this method will register the following data:
55 * <ul>
56 * <li>{@link ObjectiveFunction}</li>
57 * <li>{@link GoalType}</li>
58 * </ul>
59 * @return {@inheritDoc}
60 * @throws MathIllegalStateException if the maximal number of
61 * evaluations is exceeded.
62 */
63 @Override
64 public PointValuePair optimize(OptimizationData... optData)
65 throws MathIllegalStateException {
66 // Set up base class and perform computation.
67 return super.optimize(optData);
68 }
69
70 /**
71 * Scans the list of (required and optional) optimization data that
72 * characterize the problem.
73 *
74 * @param optData Optimization data.
75 * The following data will be looked for:
76 * <ul>
77 * <li>{@link ObjectiveFunction}</li>
78 * <li>{@link GoalType}</li>
79 * </ul>
80 */
81 @Override
82 protected void parseOptimizationData(OptimizationData... optData) {
83 // Allow base class to register its own data.
84 super.parseOptimizationData(optData);
85
86 // The existing values (as set by the previous call) are reused if
87 // not provided in the argument list.
88 for (OptimizationData data : optData) {
89 if (data instanceof GoalType) {
90 goal = (GoalType) data;
91 continue;
92 }
93 if (data instanceof ObjectiveFunction) {
94 function = ((ObjectiveFunction) data).getObjectiveFunction();
95 continue;
96 }
97 }
98 }
99
100 /** Get optimization type.
101 * @return the optimization type.
102 */
103 public GoalType getGoalType() {
104 return goal;
105 }
106
107 /**
108 * Computes the objective function value.
109 * This method <em>must</em> be called by subclasses to enforce the
110 * evaluation counter limit.
111 *
112 * @param params Point at which the objective function must be evaluated.
113 * @return the objective function value at the specified point.
114 * @throws MathIllegalStateException if the maximal number of
115 * evaluations is exceeded.
116 */
117 public double computeObjectiveValue(double[] params) {
118 super.incrementEvaluationCount();
119 return function.value(params);
120 }
121 }