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 package org.apache.commons.math4.legacy.optim.univariate;
18
19 import org.apache.commons.math4.legacy.exception.NotStrictlyPositiveException;
20 import org.apache.commons.math4.legacy.optim.AbstractConvergenceChecker;
21 import org.apache.commons.math4.core.jdkmath.JdkMath;
22
23 /**
24 * Simple implementation of the
25 * {@link org.apache.commons.math4.legacy.optim.ConvergenceChecker} interface
26 * that uses only objective function values.
27 *
28 * Convergence is considered to have been reached if either the relative
29 * difference between the objective function values is smaller than a
30 * threshold or if either the absolute difference between the objective
31 * function values is smaller than another threshold.
32 * <br>
33 * The {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)
34 * converged} method will also return {@code true} if the number of iterations
35 * has been set (see {@link #SimpleUnivariateValueChecker(double,double,int)
36 * this constructor}).
37 *
38 * @since 3.1
39 */
40 public class SimpleUnivariateValueChecker
41 extends AbstractConvergenceChecker<UnivariatePointValuePair> {
42 /**
43 * If {@link #maxIterationCount} is set to this value, the number of
44 * iterations will never cause
45 * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)}
46 * to return {@code true}.
47 */
48 private static final int ITERATION_CHECK_DISABLED = -1;
49 /**
50 * Number of iterations after which the
51 * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)}
52 * method will return true (unless the check is disabled).
53 */
54 private final int maxIterationCount;
55
56 /** Build an instance with specified thresholds.
57 *
58 * In order to perform only relative checks, the absolute tolerance
59 * must be set to a negative value. In order to perform only absolute
60 * checks, the relative tolerance must be set to a negative value.
61 *
62 * @param relativeThreshold relative tolerance threshold
63 * @param absoluteThreshold absolute tolerance threshold
64 */
65 public SimpleUnivariateValueChecker(final double relativeThreshold,
66 final double absoluteThreshold) {
67 super(relativeThreshold, absoluteThreshold);
68 maxIterationCount = ITERATION_CHECK_DISABLED;
69 }
70
71 /**
72 * Builds an instance with specified thresholds.
73 *
74 * In order to perform only relative checks, the absolute tolerance
75 * must be set to a negative value. In order to perform only absolute
76 * checks, the relative tolerance must be set to a negative value.
77 *
78 * @param relativeThreshold relative tolerance threshold
79 * @param absoluteThreshold absolute tolerance threshold
80 * @param maxIter Maximum iteration count.
81 * @throws NotStrictlyPositiveException if {@code maxIter <= 0}.
82 *
83 * @since 3.1
84 */
85 public SimpleUnivariateValueChecker(final double relativeThreshold,
86 final double absoluteThreshold,
87 final int maxIter) {
88 super(relativeThreshold, absoluteThreshold);
89
90 if (maxIter <= 0) {
91 throw new NotStrictlyPositiveException(maxIter);
92 }
93 maxIterationCount = maxIter;
94 }
95
96 /**
97 * Check if the optimization algorithm has converged considering the
98 * last two points.
99 * This method may be called several time from the same algorithm
100 * iteration with different points. This can be detected by checking the
101 * iteration number at each call if needed. Each time this method is
102 * called, the previous and current point correspond to points with the
103 * same role at each iteration, so they can be compared. As an example,
104 * simplex-based algorithms call this method for all points of the simplex,
105 * not only for the best or worst ones.
106 *
107 * @param iteration Index of current iteration
108 * @param previous Best point in the previous iteration.
109 * @param current Best point in the current iteration.
110 * @return {@code true} if the algorithm has converged.
111 */
112 @Override
113 public boolean converged(final int iteration,
114 final UnivariatePointValuePair previous,
115 final UnivariatePointValuePair current) {
116 if (maxIterationCount != ITERATION_CHECK_DISABLED && iteration >= maxIterationCount) {
117 return true;
118 }
119
120 final double p = previous.getValue();
121 final double c = current.getValue();
122 final double difference = JdkMath.abs(p - c);
123 final double size = JdkMath.max(JdkMath.abs(p), JdkMath.abs(c));
124 return difference <= size * getRelativeThreshold() ||
125 difference <= getAbsoluteThreshold();
126 }
127 }