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.math.optimization;
019    
020    import org.apache.commons.math.analysis.DifferentiableMultivariateVectorialFunction;
021    import org.apache.commons.math.FunctionEvaluationException;
022    
023    /**
024     * This interface represents an optimization algorithm for {@link DifferentiableMultivariateVectorialFunction
025     * vectorial differentiable objective functions}.
026     * <p>Optimization algorithms find the input point set that either {@link GoalType
027     * maximize or minimize} an objective function.</p>
028     * @see MultivariateRealOptimizer
029     * @see DifferentiableMultivariateRealOptimizer
030     * @version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 f??vr. 2011) $
031     * @since 2.0
032     */
033    public interface DifferentiableMultivariateVectorialOptimizer {
034    
035        /** Set the maximal number of iterations of the algorithm.
036         * @param maxIterations maximal number of function calls
037         * .
038         */
039        void setMaxIterations(int maxIterations);
040    
041        /** Get the maximal number of iterations of the algorithm.
042          * @return maximal number of iterations
043         */
044        int getMaxIterations();
045    
046        /** Get the number of iterations realized by the algorithm.
047         * @return number of iterations
048        */
049       int getIterations();
050    
051       /** Set the maximal number of functions evaluations.
052        * @param maxEvaluations maximal number of function evaluations
053        */
054       void setMaxEvaluations(int maxEvaluations);
055    
056       /** Get the maximal number of functions evaluations.
057        * @return maximal number of functions evaluations
058        */
059       int getMaxEvaluations();
060    
061        /** Get the number of evaluations of the objective function.
062         * <p>
063         * The number of evaluation correspond to the last call to the
064         * {@link #optimize(DifferentiableMultivariateVectorialFunction,
065         * double[], double[], double[]) optimize} method. It is 0 if
066         * the method has not been called yet.
067         * </p>
068         * @return number of evaluations of the objective function
069         */
070        int getEvaluations();
071    
072        /** Get the number of evaluations of the objective function jacobian .
073         * <p>
074         * The number of evaluation correspond to the last call to the
075         * {@link #optimize(DifferentiableMultivariateVectorialFunction,
076         * double[], double[], double[]) optimize} method. It is 0 if
077         * the method has not been called yet.
078         * </p>
079         * @return number of evaluations of the objective function jacobian
080         */
081        int getJacobianEvaluations();
082    
083        /** Set the convergence checker.
084         * @param checker object to use to check for convergence
085         */
086        void setConvergenceChecker(VectorialConvergenceChecker checker);
087    
088        /** Get the convergence checker.
089         * @return object used to check for convergence
090         */
091        VectorialConvergenceChecker getConvergenceChecker();
092    
093        /** Optimizes an objective function.
094         * <p>
095         * Optimization is considered to be a weighted least-squares minimization.
096         * The cost function to be minimized is
097         * &sum;weight<sub>i</sub>(objective<sub>i</sub>-target<sub>i</sub>)<sup>2</sup>
098         * </p>
099         * @param f objective function
100         * @param target target value for the objective functions at optimum
101         * @param weights weight for the least squares cost computation
102         * @param startPoint the start point for optimization
103         * @return the point/value pair giving the optimal value for objective function
104         * @exception FunctionEvaluationException if the objective function throws one during
105         * the search
106         * @exception OptimizationException if the algorithm failed to converge
107         * @exception IllegalArgumentException if the start point dimension is wrong
108         */
109        VectorialPointValuePair optimize(DifferentiableMultivariateVectorialFunction f,
110                                         double[] target, double[] weights,
111                                         double[] startPoint)
112            throws FunctionEvaluationException, OptimizationException, IllegalArgumentException;
113    
114    }