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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.math3.optim.nonlinear.scalar; import org.apache.commons.math3.analysis.MultivariateFunction; import org.apache.commons.math3.optim.BaseMultivariateOptimizer; import org.apache.commons.math3.optim.OptimizationData; import org.apache.commons.math3.optim.ConvergenceChecker; import org.apache.commons.math3.optim.PointValuePair; import org.apache.commons.math3.exception.TooManyEvaluationsException; /** * Base class for a multivariate scalar function optimizer. * * @version $Id$ * @since 3.1 */ public abstract class MultivariateOptimizer extends BaseMultivariateOptimizer<PointValuePair> { /** Objective function. */ private MultivariateFunction function; /** Type of optimization. */ private GoalType goal; /** * @param checker Convergence checker. */ protected MultivariateOptimizer(ConvergenceChecker<PointValuePair> checker) { super(checker); } /** * {@inheritDoc} * * @param optData Optimization data. The following data will be looked for: * <ul> * <li>{@link org.apache.commons.math3.optim.MaxEval}</li> * <li>{@link org.apache.commons.math3.optim.InitialGuess}</li> * <li>{@link org.apache.commons.math3.optim.SimpleBounds}</li> * <li>{@link ObjectiveFunction}</li> * <li>{@link GoalType}</li> * </ul> * @return {@inheritDoc} * @throws TooManyEvaluationsException if the maximal number of * evaluations is exceeded. */ @Override public PointValuePair optimize(OptimizationData... optData) throws TooManyEvaluationsException { // Retrieve settings. parseOptimizationData(optData); // Set up base class and perform computation. return super.optimize(optData); } /** * 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 ObjectiveFunction}</li> * <li>{@link GoalType}</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 GoalType) { goal = (GoalType) data; continue; } if (data instanceof ObjectiveFunction) { function = ((ObjectiveFunction) data).getObjectiveFunction(); continue; } } } /** * @return the optimization type. */ public GoalType getGoalType() { return goal; } /** * Computes the objective function value. * This method <em>must</em> be called by subclasses to enforce the * evaluation counter limit. * * @param params 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[] params) { super.incrementEvaluationCount(); return function.value(params); } }