    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
    018    package org.apache.commons.math3.optimization.direct;
    019
    020    import org.apache.commons.math3.util.Incrementor;
    021    import org.apache.commons.math3.exception.MaxCountExceededException;
    022    import org.apache.commons.math3.exception.TooManyEvaluationsException;
    023    import org.apache.commons.math3.analysis.MultivariateFunction;
    024    import org.apache.commons.math3.optimization.BaseMultivariateOptimizer;
    025    import org.apache.commons.math3.optimization.OptimizationData;
    026    import org.apache.commons.math3.optimization.GoalType;
    027    import org.apache.commons.math3.optimization.InitialGuess;
    028    import org.apache.commons.math3.optimization.SimpleBounds;
    029    import org.apache.commons.math3.optimization.ConvergenceChecker;
    030    import org.apache.commons.math3.optimization.PointValuePair;
    031    import org.apache.commons.math3.optimization.SimpleValueChecker;
    032    import org.apache.commons.math3.exception.DimensionMismatchException;
    033    import org.apache.commons.math3.exception.NumberIsTooSmallException;
    034    import org.apache.commons.math3.exception.NumberIsTooLargeException;
    035
    036    /**
    037     * Base class for implementing optimizers for multivariate scalar functions.
    038     * This base class handles the boiler-plate methods associated to thresholds,
    039     * evaluations counting, initial guess and simple bounds settings.
    040     *
    041     * @param <FUNC> Type of the objective function to be optimized.
    042     *
    043     * @version $Id: BaseAbstractMultivariateOptimizer.java 1422313 2012-12-15 18:53:41Z psteitz $
    044     * @deprecated As of 3.1 (to be removed in 4.0).
    045     * @since 2.2
    046     */
    047    @Deprecated
    048    public abstract class BaseAbstractMultivariateOptimizer<FUNC extends MultivariateFunction>
    049        implements BaseMultivariateOptimizer<FUNC> {
    050        /** Evaluations counter. */
    051        protected final Incrementor evaluations = new Incrementor();
    052        /** Convergence checker. */
    053        private ConvergenceChecker<PointValuePair> checker;
    054        /** Type of optimization. */
    055        private GoalType goal;
    056        /** Initial guess. */
    057        private double[] start;
    058        /** Lower bounds. */
    059        private double[] lowerBound;
    060        /** Upper bounds. */
    061        private double[] upperBound;
    062        /** Objective function. */
    063        private MultivariateFunction function;
    064
    065        /**
    066         * Simple constructor with default settings.
    067         * The convergence check is set to a {@link SimpleValueChecker}.
    068         * @deprecated See {@link SimpleValueChecker#SimpleValueChecker()}
    069         */
    070        @Deprecated
    071        protected BaseAbstractMultivariateOptimizer() {
    072            this(new SimpleValueChecker());
    073        }
    074        /**
    075         * @param checker Convergence checker.
    076         */
    077        protected BaseAbstractMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker) {
    078            this.checker = checker;
    079        }
    080
    081        /** {@inheritDoc} */
    082        public int getMaxEvaluations() {
    083            return evaluations.getMaximalCount();
    084        }
    085
    086        /** {@inheritDoc} */
    087        public int getEvaluations() {
    088            return evaluations.getCount();
    089        }
    090
    091        /** {@inheritDoc} */
    092        public ConvergenceChecker<PointValuePair> getConvergenceChecker() {
    093            return checker;
    094        }
    095
    096        /**
    097         * Compute the objective function value.
    098         *
    099         * @param point Point at which the objective function must be evaluated.
    100         * @return the objective function value at the specified point.
    101         * @throws TooManyEvaluationsException if the maximal number of
    102         * evaluations is exceeded.
    103         */
    104        protected double computeObjectiveValue(double[] point) {
    105            try {
    106                evaluations.incrementCount();
    107            } catch (MaxCountExceededException e) {
    108                throw new TooManyEvaluationsException(e.getMax());
    109            }
    110            return function.value(point);
    111        }
    112
    113        /**
    114         * {@inheritDoc}
    115         *
    116         * @deprecated As of 3.1. Please use
    117         * {@link #optimize(int,MultivariateFunction,GoalType,OptimizationData[])}
    118         * instead.
    119         */
    120        @Deprecated
    121        public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType,
    122                                       double[] startPoint) {
    123            return optimizeInternal(maxEval, f, goalType, new InitialGuess(startPoint));
    124        }
    125
    126        /**
    127         * Optimize an objective function.
    128         *
    129         * @param maxEval Allowed number of evaluations of the objective function.
    130         * @param f Objective function.
    131         * @param goalType Optimization type.
    132         * @param optData Optimization data. The following data will be looked for:
    133         * <ul>
    134         *  <li>{@link InitialGuess}</li>
    135         *  <li>{@link SimpleBounds}</li>
    136         * </ul>
    137         * @return the point/value pair giving the optimal value of the objective
    138         * function.
    139         * @since 3.1
    140         */
    141        public PointValuePair optimize(int maxEval,
    142                                       FUNC f,
    143                                       GoalType goalType,
    144                                       OptimizationData... optData) {
    145            return optimizeInternal(maxEval, f, goalType, optData);
    146        }
    147
    148        /**
    149         * Optimize an objective function.
    150         *
    151         * @param f Objective function.
    152         * @param goalType Type of optimization goal: either
    153         * {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}.
    154         * @param startPoint Start point for optimization.
    155         * @param maxEval Maximum number of function evaluations.
    156         * @return the point/value pair giving the optimal value for objective
    157         * function.
    158         * @throws org.apache.commons.math3.exception.DimensionMismatchException
    159         * if the start point dimension is wrong.
    160         * @throws org.apache.commons.math3.exception.TooManyEvaluationsException
    161         * if the maximal number of evaluations is exceeded.
    162         * @throws org.apache.commons.math3.exception.NullArgumentException if
    163         * any argument is {@code null}.
    164         * @deprecated As of 3.1. Please use
    165         * {@link #optimize(int,MultivariateFunction,GoalType,OptimizationData[])}
    166         * instead.
    167         */
    168        @Deprecated
    169        protected PointValuePair optimizeInternal(int maxEval, FUNC f, GoalType goalType,
    170                                                  double[] startPoint) {
    171            return optimizeInternal(maxEval, f, goalType, new InitialGuess(startPoint));
    172        }
    173
    174        /**
    175         * Optimize an objective function.
    176         *
    177         * @param maxEval Allowed number of evaluations of the objective function.
    178         * @param f Objective function.
    179         * @param goalType Optimization type.
    180         * @param optData Optimization data. The following data will be looked for:
    181         * <ul>
    182         *  <li>{@link InitialGuess}</li>
    183         *  <li>{@link SimpleBounds}</li>
    184         * </ul>
    185         * @return the point/value pair giving the optimal value of the objective
    186         * function.
    187         * @throws TooManyEvaluationsException if the maximal number of
    188         * evaluations is exceeded.
    189         * @since 3.1
    190         */
    191        protected PointValuePair optimizeInternal(int maxEval,
    192                                                  FUNC f,
    193                                                  GoalType goalType,
    194                                                  OptimizationData... optData)
    195            throws TooManyEvaluationsException {
    196            // Set internal state.
    197            evaluations.setMaximalCount(maxEval);
    198            evaluations.resetCount();
    199            function = f;
    200            goal = goalType;
    201            // Retrieve other settings.
    202            parseOptimizationData(optData);
    203            // Check input consistency.
    204            checkParameters();
    205            // Perform computation.
    206            return doOptimize();
    207        }
    208
    209        /**
    210         * Scans the list of (required and optional) optimization data that
    211         * characterize the problem.
    212         *
    213         * @param optData Optimization data. The following data will be looked for:
    214         * <ul>
    215         *  <li>{@link InitialGuess}</li>
    216         *  <li>{@link SimpleBounds}</li>
    217         * </ul>
    218         */
    219        private void parseOptimizationData(OptimizationData... optData) {
    220            // The existing values (as set by the previous call) are reused if
    221            // not provided in the argument list.
    222            for (OptimizationData data : optData) {
    223                if (data instanceof InitialGuess) {
    224                    start = ((InitialGuess) data).getInitialGuess();
    225                    continue;
    226                }
    227                if (data instanceof SimpleBounds) {
    228                    final SimpleBounds bounds = (SimpleBounds) data;
    229                    lowerBound = bounds.getLower();
    230                    upperBound = bounds.getUpper();
    231                    continue;
    232                }
    233            }
    234        }
    235
    236        /**
    237         * @return the optimization type.
    238         */
    239        public GoalType getGoalType() {
    240            return goal;
    241        }
    242
    243        /**
    244         * @return the initial guess.
    245         */
    246        public double[] getStartPoint() {
    247            return start == null ? null : start.clone();
    248        }
    249        /**
    250         * @return the lower bounds.
    251         * @since 3.1
    252         */
    253        public double[] getLowerBound() {
    254            return lowerBound == null ? null : lowerBound.clone();
    255        }
    256        /**
    257         * @return the upper bounds.
    258         * @since 3.1
    259         */
    260        public double[] getUpperBound() {
    261            return upperBound == null ? null : upperBound.clone();
    262        }
    263
    264        /**
    265         * Perform the bulk of the optimization algorithm.
    266         *
    267         * @return the point/value pair giving the optimal value of the
    268         * objective function.
    269         */
    270        protected abstract PointValuePair doOptimize();
    271
    272        /**
    273         * Check parameters consistency.
    274         */
    275        private void checkParameters() {
    276            if (start != null) {
    277                final int dim = start.length;
    278                if (lowerBound != null) {
    279                    if (lowerBound.length != dim) {
    280                        throw new DimensionMismatchException(lowerBound.length, dim);
    281                    }
    282                    for (int i = 0; i < dim; i++) {
    283                        final double v = start[i];
    284                        final double lo = lowerBound[i];
    285                        if (v < lo) {
    286                            throw new NumberIsTooSmallException(v, lo, true);
    287                        }
    288                    }
    289                }
    290                if (upperBound != null) {
    291                    if (upperBound.length != dim) {
    292                        throw new DimensionMismatchException(upperBound.length, dim);
    293                    }
    294                    for (int i = 0; i < dim; i++) {
    295                        final double v = start[i];
    296                        final double hi = upperBound[i];
    297                        if (v > hi) {
    298                            throw new NumberIsTooLargeException(v, hi, true);
    299                        }
    300                    }
    301                }
    302
    303                // If the bounds were not specified, the allowed interval is
    304                // assumed to be [-inf, +inf].
    305                if (lowerBound == null) {
    306                    lowerBound = new double[dim];
    307                    for (int i = 0; i < dim; i++) {
    308                        lowerBound[i] = Double.NEGATIVE_INFINITY;
    309                    }
    310                }
    311                if (upperBound == null) {
    312                    upperBound = new double[dim];
    313                    for (int i = 0; i < dim; i++) {
    314                        upperBound[i] = Double.POSITIVE_INFINITY;
    315                    }
    316                }
    317            }
    318        }
    319    }