BaseAbstractMultivariateOptimizer.java
- /*
- * 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.math3.optimization.direct;
- import org.apache.commons.math3.util.Incrementor;
- import org.apache.commons.math3.exception.MaxCountExceededException;
- import org.apache.commons.math3.exception.TooManyEvaluationsException;
- import org.apache.commons.math3.analysis.MultivariateFunction;
- import org.apache.commons.math3.optimization.BaseMultivariateOptimizer;
- import org.apache.commons.math3.optimization.OptimizationData;
- import org.apache.commons.math3.optimization.GoalType;
- import org.apache.commons.math3.optimization.InitialGuess;
- import org.apache.commons.math3.optimization.SimpleBounds;
- import org.apache.commons.math3.optimization.ConvergenceChecker;
- import org.apache.commons.math3.optimization.PointValuePair;
- import org.apache.commons.math3.optimization.SimpleValueChecker;
- import org.apache.commons.math3.exception.DimensionMismatchException;
- import org.apache.commons.math3.exception.NumberIsTooSmallException;
- import org.apache.commons.math3.exception.NumberIsTooLargeException;
- /**
- * Base class for implementing optimizers for multivariate scalar functions.
- * This base class handles the boiler-plate methods associated to thresholds,
- * evaluations counting, initial guess and simple bounds settings.
- *
- * @param <FUNC> Type of the objective function to be optimized.
- *
- * @deprecated As of 3.1 (to be removed in 4.0).
- * @since 2.2
- */
- @Deprecated
- public abstract class BaseAbstractMultivariateOptimizer<FUNC extends MultivariateFunction>
- implements BaseMultivariateOptimizer<FUNC> {
- /** Evaluations counter. */
- protected final Incrementor evaluations = new Incrementor();
- /** Convergence checker. */
- private ConvergenceChecker<PointValuePair> checker;
- /** Type of optimization. */
- private GoalType goal;
- /** Initial guess. */
- private double[] start;
- /** Lower bounds. */
- private double[] lowerBound;
- /** Upper bounds. */
- private double[] upperBound;
- /** Objective function. */
- private MultivariateFunction function;
- /**
- * Simple constructor with default settings.
- * The convergence check is set to a {@link SimpleValueChecker}.
- * @deprecated See {@link SimpleValueChecker#SimpleValueChecker()}
- */
- @Deprecated
- protected BaseAbstractMultivariateOptimizer() {
- this(new SimpleValueChecker());
- }
- /**
- * @param checker Convergence checker.
- */
- protected BaseAbstractMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker) {
- this.checker = checker;
- }
- /** {@inheritDoc} */
- public int getMaxEvaluations() {
- return evaluations.getMaximalCount();
- }
- /** {@inheritDoc} */
- public int getEvaluations() {
- return evaluations.getCount();
- }
- /** {@inheritDoc} */
- public ConvergenceChecker<PointValuePair> getConvergenceChecker() {
- return checker;
- }
- /**
- * Compute the objective function value.
- *
- * @param point Point at which the objective function must be evaluated.
- * @return the objective function value at the specified point.
- * @throws TooManyEvaluationsException if the maximal number of
- * evaluations is exceeded.
- */
- protected double computeObjectiveValue(double[] point) {
- try {
- evaluations.incrementCount();
- } catch (MaxCountExceededException e) {
- throw new TooManyEvaluationsException(e.getMax());
- }
- return function.value(point);
- }
- /**
- * {@inheritDoc}
- *
- * @deprecated As of 3.1. Please use
- * {@link #optimize(int,MultivariateFunction,GoalType,OptimizationData[])}
- * instead.
- */
- @Deprecated
- public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType,
- double[] startPoint) {
- return optimizeInternal(maxEval, f, goalType, new InitialGuess(startPoint));
- }
- /**
- * Optimize an objective function.
- *
- * @param maxEval Allowed number of evaluations of the objective function.
- * @param f Objective function.
- * @param goalType Optimization type.
- * @param optData Optimization data. The following data will be looked for:
- * <ul>
- * <li>{@link InitialGuess}</li>
- * <li>{@link SimpleBounds}</li>
- * </ul>
- * @return the point/value pair giving the optimal value of the objective
- * function.
- * @since 3.1
- */
- public PointValuePair optimize(int maxEval,
- FUNC f,
- GoalType goalType,
- OptimizationData... optData) {
- return optimizeInternal(maxEval, f, goalType, optData);
- }
- /**
- * Optimize an objective function.
- *
- * @param f Objective function.
- * @param goalType Type of optimization goal: either
- * {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}.
- * @param startPoint Start point for optimization.
- * @param maxEval Maximum number of function evaluations.
- * @return the point/value pair giving the optimal value for objective
- * function.
- * @throws org.apache.commons.math3.exception.DimensionMismatchException
- * if the start point dimension is wrong.
- * @throws org.apache.commons.math3.exception.TooManyEvaluationsException
- * if the maximal number of evaluations is exceeded.
- * @throws org.apache.commons.math3.exception.NullArgumentException if
- * any argument is {@code null}.
- * @deprecated As of 3.1. Please use
- * {@link #optimize(int,MultivariateFunction,GoalType,OptimizationData[])}
- * instead.
- */
- @Deprecated
- protected PointValuePair optimizeInternal(int maxEval, FUNC f, GoalType goalType,
- double[] startPoint) {
- return optimizeInternal(maxEval, f, goalType, new InitialGuess(startPoint));
- }
- /**
- * Optimize an objective function.
- *
- * @param maxEval Allowed number of evaluations of the objective function.
- * @param f Objective function.
- * @param goalType Optimization type.
- * @param optData Optimization data. The following data will be looked for:
- * <ul>
- * <li>{@link InitialGuess}</li>
- * <li>{@link SimpleBounds}</li>
- * </ul>
- * @return the point/value pair giving the optimal value of the objective
- * function.
- * @throws TooManyEvaluationsException if the maximal number of
- * evaluations is exceeded.
- * @since 3.1
- */
- protected PointValuePair optimizeInternal(int maxEval,
- FUNC f,
- GoalType goalType,
- OptimizationData... optData)
- throws TooManyEvaluationsException {
- // Set internal state.
- evaluations.setMaximalCount(maxEval);
- evaluations.resetCount();
- function = f;
- goal = goalType;
- // Retrieve other settings.
- parseOptimizationData(optData);
- // Check input consistency.
- checkParameters();
- // Perform computation.
- return doOptimize();
- }
- /**
- * Scans the list of (required and optional) optimization data that
- * characterize the problem.
- *
- * @param optData Optimization data. The following data will be looked for:
- * <ul>
- * <li>{@link InitialGuess}</li>
- * <li>{@link SimpleBounds}</li>
- * </ul>
- */
- private void parseOptimizationData(OptimizationData... optData) {
- // The existing values (as set by the previous call) are reused if
- // not provided in the argument list.
- for (OptimizationData data : optData) {
- if (data instanceof InitialGuess) {
- start = ((InitialGuess) data).getInitialGuess();
- continue;
- }
- if (data instanceof SimpleBounds) {
- final SimpleBounds bounds = (SimpleBounds) data;
- lowerBound = bounds.getLower();
- upperBound = bounds.getUpper();
- continue;
- }
- }
- }
- /**
- * @return the optimization type.
- */
- public GoalType getGoalType() {
- return goal;
- }
- /**
- * @return the initial guess.
- */
- public double[] getStartPoint() {
- return start == null ? null : start.clone();
- }
- /**
- * @return the lower bounds.
- * @since 3.1
- */
- public double[] getLowerBound() {
- return lowerBound == null ? null : lowerBound.clone();
- }
- /**
- * @return the upper bounds.
- * @since 3.1
- */
- public double[] getUpperBound() {
- return upperBound == null ? null : upperBound.clone();
- }
- /**
- * Perform the bulk of the optimization algorithm.
- *
- * @return the point/value pair giving the optimal value of the
- * objective function.
- */
- protected abstract PointValuePair doOptimize();
- /**
- * Check parameters consistency.
- */
- private void checkParameters() {
- if (start != null) {
- final int dim = start.length;
- if (lowerBound != null) {
- if (lowerBound.length != dim) {
- throw new DimensionMismatchException(lowerBound.length, dim);
- }
- for (int i = 0; i < dim; i++) {
- final double v = start[i];
- final double lo = lowerBound[i];
- if (v < lo) {
- throw new NumberIsTooSmallException(v, lo, true);
- }
- }
- }
- if (upperBound != null) {
- if (upperBound.length != dim) {
- throw new DimensionMismatchException(upperBound.length, dim);
- }
- for (int i = 0; i < dim; i++) {
- final double v = start[i];
- final double hi = upperBound[i];
- if (v > hi) {
- throw new NumberIsTooLargeException(v, hi, true);
- }
- }
- }
- // If the bounds were not specified, the allowed interval is
- // assumed to be [-inf, +inf].
- if (lowerBound == null) {
- lowerBound = new double[dim];
- for (int i = 0; i < dim; i++) {
- lowerBound[i] = Double.NEGATIVE_INFINITY;
- }
- }
- if (upperBound == null) {
- upperBound = new double[dim];
- for (int i = 0; i < dim; i++) {
- upperBound[i] = Double.POSITIVE_INFINITY;
- }
- }
- }
- }
- }