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;
23
24 import org.hipparchus.exception.LocalizedCoreFormats;
25 import org.hipparchus.exception.MathIllegalArgumentException;
26
27 /**
28 * Base class for implementing optimizers for multivariate functions.
29 * It contains the boiler-plate code for initial guess and bounds
30 * specifications.
31 * <em>It is not a "user" class.</em>
32 *
33 * @param <P> Type of the point/value pair returned by the optimization
34 * algorithm.
35 *
36 */
37 public abstract class BaseMultivariateOptimizer<P>
38 extends BaseOptimizer<P> {
39 /** Initial guess. */
40 private double[] start;
41 /** Lower bounds. */
42 private double[] lowerBound;
43 /** Upper bounds. */
44 private double[] upperBound;
45
46 /** Simple constructor.
47 * @param checker Convergence checker.
48 */
49 protected BaseMultivariateOptimizer(ConvergenceChecker<P> checker) {
50 super(checker);
51 }
52
53 /**
54 * {@inheritDoc}
55 *
56 * @param optData Optimization data. In addition to those documented in
57 * {@link BaseOptimizer#parseOptimizationData(OptimizationData[]) BaseOptimizer},
58 * this method will register the following data:
59 * <ul>
60 * <li>{@link InitialGuess}</li>
61 * <li>{@link SimpleBounds}</li>
62 * </ul>
63 * @return {@inheritDoc}
64 */
65 @Override
66 public P optimize(OptimizationData... optData) {
67 // Perform optimization.
68 return super.optimize(optData);
69 }
70
71 /**
72 * Scans the list of (required and optional) optimization data that
73 * characterize the problem.
74 *
75 * @param optData Optimization data. The following data will be looked for:
76 * <ul>
77 * <li>{@link InitialGuess}</li>
78 * <li>{@link SimpleBounds}</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 InitialGuess) {
90 start = ((InitialGuess) data).getInitialGuess();
91 continue;
92 }
93 if (data instanceof SimpleBounds) {
94 final SimpleBounds bounds = (SimpleBounds) data;
95 lowerBound = bounds.getLower();
96 upperBound = bounds.getUpper();
97 continue;
98 }
99 }
100
101 // Check input consistency.
102 checkParameters();
103 }
104
105 /**
106 * Gets the initial guess.
107 *
108 * @return the initial guess, or {@code null} if not set.
109 */
110 public double[] getStartPoint() {
111 return start == null ? null : start.clone();
112 }
113 /** Get lower bounds.
114 * @return the lower bounds, or {@code null} if not set.
115 */
116 public double[] getLowerBound() {
117 return lowerBound == null ? null : lowerBound.clone();
118 }
119 /** Get upper bounds.
120 * @return the upper bounds, or {@code null} if not set.
121 */
122 public double[] getUpperBound() {
123 return upperBound == null ? null : upperBound.clone();
124 }
125
126 /**
127 * Check parameters consistency.
128 */
129 private void checkParameters() {
130 if (start != null) {
131 final int dim = start.length;
132 if (lowerBound != null) {
133 if (lowerBound.length != dim) {
134 throw new MathIllegalArgumentException(LocalizedCoreFormats.DIMENSIONS_MISMATCH,
135 lowerBound.length, dim);
136 }
137 for (int i = 0; i < dim; i++) {
138 final double v = start[i];
139 final double lo = lowerBound[i];
140 if (v < lo) {
141 throw new MathIllegalArgumentException(LocalizedCoreFormats.NUMBER_TOO_SMALL,
142 v, lo);
143 }
144 }
145 }
146 if (upperBound != null) {
147 if (upperBound.length != dim) {
148 throw new MathIllegalArgumentException(LocalizedCoreFormats.DIMENSIONS_MISMATCH,
149 upperBound.length, dim);
150 }
151 for (int i = 0; i < dim; i++) {
152 final double v = start[i];
153 final double hi = upperBound[i];
154 if (v > hi) {
155 throw new MathIllegalArgumentException(LocalizedCoreFormats.NUMBER_TOO_LARGE,
156 v, hi);
157 }
158 }
159 }
160 }
161 }
162 }