/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ /* * This is not the original file distributed by the Apache Software Foundation * It has been modified by the Hipparchus project */ package org.hipparchus.optim.univariate; import org.hipparchus.exception.LocalizedCoreFormats; import org.hipparchus.exception.MathIllegalArgumentException; import org.hipparchus.optim.AbstractConvergenceChecker; import org.hipparchus.util.FastMath; /** * Simple implementation of the * {@link org.hipparchus.optim.ConvergenceChecker} interface * that uses only objective function values. * * Convergence is considered to have been reached if either the relative * difference between the objective function values is smaller than a * threshold or if either the absolute difference between the objective * function values is smaller than another threshold. * <br/> * The {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair) * converged} method will also return {@code true} if the number of iterations * has been set (see {@link #SimpleUnivariateValueChecker(double,double,int) * this constructor}). * */ public class SimpleUnivariateValueChecker extends AbstractConvergenceChecker<UnivariatePointValuePair> { /** * If {@link #maxIterationCount} is set to this value, the number of * iterations will never cause * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)} * to return {@code true}. */ private static final int ITERATION_CHECK_DISABLED = -1; /** * Number of iterations after which the * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)} * method will return true (unless the check is disabled). */ private final int maxIterationCount; /** Build an instance with specified thresholds. * * In order to perform only relative checks, the absolute tolerance * must be set to a negative value. In order to perform only absolute * checks, the relative tolerance must be set to a negative value. * * @param relativeThreshold relative tolerance threshold * @param absoluteThreshold absolute tolerance threshold */ public SimpleUnivariateValueChecker(final double relativeThreshold, final double absoluteThreshold) { super(relativeThreshold, absoluteThreshold); maxIterationCount = ITERATION_CHECK_DISABLED; } /** * Builds an instance with specified thresholds. * * In order to perform only relative checks, the absolute tolerance * must be set to a negative value. In order to perform only absolute * checks, the relative tolerance must be set to a negative value. * * @param relativeThreshold relative tolerance threshold * @param absoluteThreshold absolute tolerance threshold * @param maxIter Maximum iteration count. * @throws MathIllegalArgumentException if {@code maxIter <= 0}. * */ public SimpleUnivariateValueChecker(final double relativeThreshold, final double absoluteThreshold, final int maxIter) { super(relativeThreshold, absoluteThreshold); if (maxIter <= 0) { throw new MathIllegalArgumentException(LocalizedCoreFormats.NUMBER_TOO_SMALL_BOUND_EXCLUDED, maxIter, 0); } maxIterationCount = maxIter; } /** * Check if the optimization algorithm has converged considering the * last two points. * This method may be called several time from the same algorithm * iteration with different points. This can be detected by checking the * iteration number at each call if needed. Each time this method is * called, the previous and current point correspond to points with the * same role at each iteration, so they can be compared. As an example, * simplex-based algorithms call this method for all points of the simplex, * not only for the best or worst ones. * * @param iteration Index of current iteration * @param previous Best point in the previous iteration. * @param current Best point in the current iteration. * @return {@code true} if the algorithm has converged. */ @Override public boolean converged(final int iteration, final UnivariatePointValuePair previous, final UnivariatePointValuePair current) { if (maxIterationCount != ITERATION_CHECK_DISABLED && iteration >= maxIterationCount) { return true; } final double p = previous.getValue(); final double c = current.getValue(); final double difference = FastMath.abs(p - c); final double size = FastMath.max(FastMath.abs(p), FastMath.abs(c)); return difference <= size * getRelativeThreshold() || difference <= getAbsoluteThreshold(); } }