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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  
18  package org.apache.commons.math3.optimization.univariate;
19  
20  import org.apache.commons.math3.util.FastMath;
21  import org.apache.commons.math3.exception.NotStrictlyPositiveException;
22  import org.apache.commons.math3.optimization.AbstractConvergenceChecker;
23  
24  /**
25   * Simple implementation of the
26   * {@link org.apache.commons.math3.optimization.ConvergenceChecker} interface
27   * that uses only objective function values.
28   *
29   * Convergence is considered to have been reached if either the relative
30   * difference between the objective function values is smaller than a
31   * threshold or if either the absolute difference between the objective
32   * function values is smaller than another threshold.
33   * <br/>
34   * The {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)
35   * converged} method will also return {@code true} if the number of iterations
36   * has been set (see {@link #SimpleUnivariateValueChecker(double,double,int)
37   * this constructor}).
38   *
39   * @deprecated As of 3.1 (to be removed in 4.0).
40   * @since 3.1
41   */
42  @Deprecated
43  public class SimpleUnivariateValueChecker
44      extends AbstractConvergenceChecker<UnivariatePointValuePair> {
45      /**
46       * If {@link #maxIterationCount} is set to this value, the number of
47       * iterations will never cause
48       * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)}
49       * to return {@code true}.
50       */
51      private static final int ITERATION_CHECK_DISABLED = -1;
52      /**
53       * Number of iterations after which the
54       * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)}
55       * method will return true (unless the check is disabled).
56       */
57      private final int maxIterationCount;
58  
59      /**
60       * Build an instance with default thresholds.
61       * @deprecated See {@link AbstractConvergenceChecker#AbstractConvergenceChecker()}
62       */
63      @Deprecated
64      public SimpleUnivariateValueChecker() {
65          maxIterationCount = ITERATION_CHECK_DISABLED;
66      }
67  
68      /** Build an instance with specified thresholds.
69       *
70       * In order to perform only relative checks, the absolute tolerance
71       * must be set to a negative value. In order to perform only absolute
72       * checks, the relative tolerance must be set to a negative value.
73       *
74       * @param relativeThreshold relative tolerance threshold
75       * @param absoluteThreshold absolute tolerance threshold
76       */
77      public SimpleUnivariateValueChecker(final double relativeThreshold,
78                                          final double absoluteThreshold) {
79          super(relativeThreshold, absoluteThreshold);
80          maxIterationCount = ITERATION_CHECK_DISABLED;
81      }
82  
83      /**
84       * Builds an instance with specified thresholds.
85       *
86       * In order to perform only relative checks, the absolute tolerance
87       * must be set to a negative value. In order to perform only absolute
88       * checks, the relative tolerance must be set to a negative value.
89       *
90       * @param relativeThreshold relative tolerance threshold
91       * @param absoluteThreshold absolute tolerance threshold
92       * @param maxIter Maximum iteration count.
93       * @throws NotStrictlyPositiveException if {@code maxIter <= 0}.
94       *
95       * @since 3.1
96       */
97      public SimpleUnivariateValueChecker(final double relativeThreshold,
98                                          final double absoluteThreshold,
99                                          final int maxIter) {
100         super(relativeThreshold, absoluteThreshold);
101 
102         if (maxIter <= 0) {
103             throw new NotStrictlyPositiveException(maxIter);
104         }
105         maxIterationCount = maxIter;
106     }
107 
108     /**
109      * Check if the optimization algorithm has converged considering the
110      * last two points.
111      * This method may be called several time from the same algorithm
112      * iteration with different points. This can be detected by checking the
113      * iteration number at each call if needed. Each time this method is
114      * called, the previous and current point correspond to points with the
115      * same role at each iteration, so they can be compared. As an example,
116      * simplex-based algorithms call this method for all points of the simplex,
117      * not only for the best or worst ones.
118      *
119      * @param iteration Index of current iteration
120      * @param previous Best point in the previous iteration.
121      * @param current Best point in the current iteration.
122      * @return {@code true} if the algorithm has converged.
123      */
124     @Override
125     public boolean converged(final int iteration,
126                              final UnivariatePointValuePair previous,
127                              final UnivariatePointValuePair current) {
128         if (maxIterationCount != ITERATION_CHECK_DISABLED && iteration >= maxIterationCount) {
129             return true;
130         }
131 
132         final double p = previous.getValue();
133         final double c = current.getValue();
134         final double difference = FastMath.abs(p - c);
135         final double size = FastMath.max(FastMath.abs(p), FastMath.abs(c));
136         return difference <= size * getRelativeThreshold() ||
137             difference <= getAbsoluteThreshold();
138     }
139 }