source: src/main/java/agents/anac/y2019/harddealer/math3/optim/univariate/UnivariateOptimizer.java

Last change on this file was 204, checked in by Katsuhide Fujita, 5 years ago

Fixed errors of ANAC2019 agents

  • Property svn:executable set to *
File size: 4.9 KB
Line 
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 */
17package agents.anac.y2019.harddealer.math3.optim.univariate;
18
19import agents.anac.y2019.harddealer.math3.analysis.UnivariateFunction;
20import agents.anac.y2019.harddealer.math3.optim.BaseOptimizer;
21import agents.anac.y2019.harddealer.math3.optim.OptimizationData;
22import agents.anac.y2019.harddealer.math3.optim.nonlinear.scalar.GoalType;
23import agents.anac.y2019.harddealer.math3.optim.ConvergenceChecker;
24import agents.anac.y2019.harddealer.math3.exception.TooManyEvaluationsException;
25
26/**
27 * Base class for a univariate scalar function optimizer.
28 *
29 * @since 3.1
30 */
31public abstract class UnivariateOptimizer
32 extends BaseOptimizer<UnivariatePointValuePair> {
33 /** Objective function. */
34 private UnivariateFunction function;
35 /** Type of optimization. */
36 private GoalType goal;
37 /** Initial guess. */
38 private double start;
39 /** Lower bound. */
40 private double min;
41 /** Upper bound. */
42 private double max;
43
44 /**
45 * @param checker Convergence checker.
46 */
47 protected UnivariateOptimizer(ConvergenceChecker<UnivariatePointValuePair> checker) {
48 super(checker);
49 }
50
51 /**
52 * {@inheritDoc}
53 *
54 * @param optData Optimization data. In addition to those documented in
55 * {@link BaseOptimizer#parseOptimizationData(OptimizationData[])
56 * BaseOptimizer}, this method will register the following data:
57 * <ul>
58 * <li>{@link GoalType}</li>
59 * <li>{@link SearchInterval}</li>
60 * <li>{@link UnivariateObjectiveFunction}</li>
61 * </ul>
62 * @return {@inheritDoc}
63 * @throws TooManyEvaluationsException if the maximal number of
64 * evaluations is exceeded.
65 */
66 @Override
67 public UnivariatePointValuePair optimize(OptimizationData... optData)
68 throws TooManyEvaluationsException {
69 // Perform computation.
70 return super.optimize(optData);
71 }
72
73 /**
74 * @return the optimization type.
75 */
76 public GoalType getGoalType() {
77 return goal;
78 }
79
80 /**
81 * Scans the list of (required and optional) optimization data that
82 * characterize the problem.
83 *
84 * @param optData Optimization data.
85 * The following data will be looked for:
86 * <ul>
87 * <li>{@link GoalType}</li>
88 * <li>{@link SearchInterval}</li>
89 * <li>{@link UnivariateObjectiveFunction}</li>
90 * </ul>
91 */
92 @Override
93 protected void parseOptimizationData(OptimizationData... optData) {
94 // Allow base class to register its own data.
95 super.parseOptimizationData(optData);
96
97 // The existing values (as set by the previous call) are reused if
98 // not provided in the argument list.
99 for (OptimizationData data : optData) {
100 if (data instanceof SearchInterval) {
101 final SearchInterval interval = (SearchInterval) data;
102 min = interval.getMin();
103 max = interval.getMax();
104 start = interval.getStartValue();
105 continue;
106 }
107 if (data instanceof UnivariateObjectiveFunction) {
108 function = ((UnivariateObjectiveFunction) data).getObjectiveFunction();
109 continue;
110 }
111 if (data instanceof GoalType) {
112 goal = (GoalType) data;
113 continue;
114 }
115 }
116 }
117
118 /**
119 * @return the initial guess.
120 */
121 public double getStartValue() {
122 return start;
123 }
124 /**
125 * @return the lower bounds.
126 */
127 public double getMin() {
128 return min;
129 }
130 /**
131 * @return the upper bounds.
132 */
133 public double getMax() {
134 return max;
135 }
136
137 /**
138 * Computes the objective function value.
139 * This method <em>must</em> be called by subclasses to enforce the
140 * evaluation counter limit.
141 *
142 * @param x Point at which the objective function must be evaluated.
143 * @return the objective function value at the specified point.
144 * @throws TooManyEvaluationsException if the maximal number of
145 * evaluations is exceeded.
146 */
147 protected double computeObjectiveValue(double x) {
148 super.incrementEvaluationCount();
149 return function.value(x);
150 }
151}
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