001/* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017package org.apache.commons.math3.optim.univariate; 018 019import org.apache.commons.math3.util.FastMath; 020import org.apache.commons.math3.exception.NotStrictlyPositiveException; 021import org.apache.commons.math3.optim.AbstractConvergenceChecker; 022 023/** 024 * Simple implementation of the 025 * {@link org.apache.commons.math3.optimization.ConvergenceChecker} interface 026 * that uses only objective function values. 027 * 028 * Convergence is considered to have been reached if either the relative 029 * difference between the objective function values is smaller than a 030 * threshold or if either the absolute difference between the objective 031 * function values is smaller than another threshold. 032 * <br/> 033 * The {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair) 034 * converged} method will also return {@code true} if the number of iterations 035 * has been set (see {@link #SimpleUnivariateValueChecker(double,double,int) 036 * this constructor}). 037 * 038 * @since 3.1 039 */ 040public class SimpleUnivariateValueChecker 041 extends AbstractConvergenceChecker<UnivariatePointValuePair> { 042 /** 043 * If {@link #maxIterationCount} is set to this value, the number of 044 * iterations will never cause 045 * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)} 046 * to return {@code true}. 047 */ 048 private static final int ITERATION_CHECK_DISABLED = -1; 049 /** 050 * Number of iterations after which the 051 * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)} 052 * method will return true (unless the check is disabled). 053 */ 054 private final int maxIterationCount; 055 056 /** Build an instance with specified thresholds. 057 * 058 * In order to perform only relative checks, the absolute tolerance 059 * must be set to a negative value. In order to perform only absolute 060 * checks, the relative tolerance must be set to a negative value. 061 * 062 * @param relativeThreshold relative tolerance threshold 063 * @param absoluteThreshold absolute tolerance threshold 064 */ 065 public SimpleUnivariateValueChecker(final double relativeThreshold, 066 final double absoluteThreshold) { 067 super(relativeThreshold, absoluteThreshold); 068 maxIterationCount = ITERATION_CHECK_DISABLED; 069 } 070 071 /** 072 * Builds an instance with specified thresholds. 073 * 074 * In order to perform only relative checks, the absolute tolerance 075 * must be set to a negative value. In order to perform only absolute 076 * checks, the relative tolerance must be set to a negative value. 077 * 078 * @param relativeThreshold relative tolerance threshold 079 * @param absoluteThreshold absolute tolerance threshold 080 * @param maxIter Maximum iteration count. 081 * @throws NotStrictlyPositiveException if {@code maxIter <= 0}. 082 * 083 * @since 3.1 084 */ 085 public SimpleUnivariateValueChecker(final double relativeThreshold, 086 final double absoluteThreshold, 087 final int maxIter) { 088 super(relativeThreshold, absoluteThreshold); 089 090 if (maxIter <= 0) { 091 throw new NotStrictlyPositiveException(maxIter); 092 } 093 maxIterationCount = maxIter; 094 } 095 096 /** 097 * Check if the optimization algorithm has converged considering the 098 * last two points. 099 * 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 = FastMath.abs(p - c); 123 final double size = FastMath.max(FastMath.abs(p), FastMath.abs(c)); 124 return difference <= size * getRelativeThreshold() || 125 difference <= getAbsoluteThreshold(); 126 } 127}