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 */
017
018package org.apache.commons.math3.optimization;
019
020import org.apache.commons.math3.util.FastMath;
021import org.apache.commons.math3.exception.NotStrictlyPositiveException;
022
023/**
024 * Simple implementation of the {@link ConvergenceChecker} interface using
025 * only objective function values.
026 *
027 * Convergence is considered to have been reached if either the relative
028 * difference between the objective function values is smaller than a
029 * threshold or if either the absolute difference between the objective
030 * function values is smaller than another threshold for all vectors elements.
031 * <br/>
032 * The {@link #converged(int,PointVectorValuePair,PointVectorValuePair) converged}
033 * method will also return {@code true} if the number of iterations has been set
034 * (see {@link #SimpleVectorValueChecker(double,double,int) this constructor}).
035 *
036 * @version $Id: SimpleVectorValueChecker.java 1462503 2013-03-29 15:48:27Z luc $
037 * @deprecated As of 3.1 (to be removed in 4.0).
038 * @since 3.0
039 */
040@Deprecated
041public class SimpleVectorValueChecker
042    extends AbstractConvergenceChecker<PointVectorValuePair> {
043    /**
044     * If {@link #maxIterationCount} is set to this value, the number of
045     * iterations will never cause
046     * {@link #converged(int,PointVectorValuePair,PointVectorValuePair)}
047     * to return {@code true}.
048     */
049    private static final int ITERATION_CHECK_DISABLED = -1;
050    /**
051     * Number of iterations after which the
052     * {@link #converged(int,PointVectorValuePair,PointVectorValuePair)} method
053     * will return true (unless the check is disabled).
054     */
055    private final int maxIterationCount;
056
057    /**
058     * Build an instance with default thresholds.
059     * @deprecated See {@link AbstractConvergenceChecker#AbstractConvergenceChecker()}
060     */
061    @Deprecated
062    public SimpleVectorValueChecker() {
063        maxIterationCount = ITERATION_CHECK_DISABLED;
064    }
065
066    /**
067     * Build an instance with specified thresholds.
068     *
069     * In order to perform only relative checks, the absolute tolerance
070     * must be set to a negative value. In order to perform only absolute
071     * checks, the relative tolerance must be set to a negative value.
072     *
073     * @param relativeThreshold relative tolerance threshold
074     * @param absoluteThreshold absolute tolerance threshold
075     */
076    public SimpleVectorValueChecker(final double relativeThreshold,
077                                    final double absoluteThreshold) {
078        super(relativeThreshold, absoluteThreshold);
079        maxIterationCount = ITERATION_CHECK_DISABLED;
080    }
081
082    /**
083     * Builds an instance with specified tolerance thresholds and
084     * iteration count.
085     *
086     * In order to perform only relative checks, the absolute tolerance
087     * must be set to a negative value. In order to perform only absolute
088     * checks, the relative tolerance must be set to a negative value.
089     *
090     * @param relativeThreshold Relative tolerance threshold.
091     * @param absoluteThreshold Absolute tolerance threshold.
092     * @param maxIter Maximum iteration count.
093     * @throws NotStrictlyPositiveException if {@code maxIter <= 0}.
094     *
095     * @since 3.1
096     */
097    public SimpleVectorValueChecker(final double relativeThreshold,
098                                    final double absoluteThreshold,
099                                    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 times 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 arguments satify the convergence criterion.
123     */
124    @Override
125    public boolean converged(final int iteration,
126                             final PointVectorValuePair previous,
127                             final PointVectorValuePair current) {
128        if (maxIterationCount != ITERATION_CHECK_DISABLED && iteration >= maxIterationCount) {
129            return true;
130        }
131
132        final double[] p = previous.getValueRef();
133        final double[] c = current.getValueRef();
134        for (int i = 0; i < p.length; ++i) {
135            final double pi         = p[i];
136            final double ci         = c[i];
137            final double difference = FastMath.abs(pi - ci);
138            final double size       = FastMath.max(FastMath.abs(pi), FastMath.abs(ci));
139            if (difference > size * getRelativeThreshold() &&
140                difference > getAbsoluteThreshold()) {
141                return false;
142            }
143        }
144        return true;
145    }
146}