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/*
* 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.
*/
package org.apache.commons.math4.legacy.optim;
import org.apache.commons.math4.legacy.exception.NotStrictlyPositiveException;
import org.apache.commons.math4.legacy.core.jdkmath.AccurateMath;
/**
* Simple implementation of the {@link ConvergenceChecker} interface using
* 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 for all vectors elements.
* <br>
* The {@link #converged(int,PointVectorValuePair,PointVectorValuePair) converged}
* method will also return {@code true} if the number of iterations has been set
* (see {@link #SimpleVectorValueChecker(double,double,int) this constructor}).
*
* @since 3.0
*/
public class SimpleVectorValueChecker
extends AbstractConvergenceChecker<PointVectorValuePair> {
/**
* If {@link #maxIterationCount} is set to this value, the number of
* iterations will never cause
* {@link #converged(int,PointVectorValuePair,PointVectorValuePair)}
* to return {@code true}.
*/
private static final int ITERATION_CHECK_DISABLED = -1;
/**
* Number of iterations after which the
* {@link #converged(int,PointVectorValuePair,PointVectorValuePair)} 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 SimpleVectorValueChecker(final double relativeThreshold,
final double absoluteThreshold) {
super(relativeThreshold, absoluteThreshold);
maxIterationCount = ITERATION_CHECK_DISABLED;
}
/**
* Builds an instance with specified tolerance thresholds and
* iteration count.
*
* 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 NotStrictlyPositiveException if {@code maxIter <= 0}.
*
* @since 3.1
*/
public SimpleVectorValueChecker(final double relativeThreshold,
final double absoluteThreshold,
final int maxIter) {
super(relativeThreshold, absoluteThreshold);
if (maxIter <= 0) {
throw new NotStrictlyPositiveException(maxIter);
}
maxIterationCount = maxIter;
}
/**
* Check if the optimization algorithm has converged considering the
* last two points.
* This method may be called several times 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 arguments satisfy the convergence criterion.
*/
@Override
public boolean converged(final int iteration,
final PointVectorValuePair previous,
final PointVectorValuePair current) {
if (maxIterationCount != ITERATION_CHECK_DISABLED && iteration >= maxIterationCount) {
return true;
}
final double[] p = previous.getValueRef();
final double[] c = current.getValueRef();
for (int i = 0; i < p.length; ++i) {
final double pi = p[i];
final double ci = c[i];
final double difference = AccurateMath.abs(pi - ci);
final double size = AccurateMath.max(AccurateMath.abs(pi), AccurateMath.abs(ci));
if (difference > size * getRelativeThreshold() &&
difference > getAbsoluteThreshold()) {
return false;
}
}
return true;
}
}