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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.math.optimization;
import org.apache.commons.math.analysis.DifferentiableMultivariateVectorialFunction;
import org.apache.commons.math.FunctionEvaluationException;
/**
* This interface represents an optimization algorithm for {@link DifferentiableMultivariateVectorialFunction
* vectorial differentiable objective functions}.
* <p>Optimization algorithms find the input point set that either {@link GoalType
* maximize or minimize} an objective function.</p>
* @see MultivariateRealOptimizer
* @see DifferentiableMultivariateRealOptimizer
* @version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $
* @since 2.0
*/
public interface DifferentiableMultivariateVectorialOptimizer {
/** Set the maximal number of iterations of the algorithm.
* @param maxIterations maximal number of function calls
* .
*/
void setMaxIterations(int maxIterations);
/** Get the maximal number of iterations of the algorithm.
* @return maximal number of iterations
*/
int getMaxIterations();
/** Get the number of iterations realized by the algorithm.
* @return number of iterations
*/
int getIterations();
/** Set the maximal number of functions evaluations.
* @param maxEvaluations maximal number of function evaluations
*/
void setMaxEvaluations(int maxEvaluations);
/** Get the maximal number of functions evaluations.
* @return maximal number of functions evaluations
*/
int getMaxEvaluations();
/** Get the number of evaluations of the objective function.
* <p>
* The number of evaluation correspond to the last call to the
* {@link #optimize(DifferentiableMultivariateVectorialFunction,
* double[], double[], double[]) optimize} method. It is 0 if
* the method has not been called yet.
* </p>
* @return number of evaluations of the objective function
*/
int getEvaluations();
/** Get the number of evaluations of the objective function jacobian .
* <p>
* The number of evaluation correspond to the last call to the
* {@link #optimize(DifferentiableMultivariateVectorialFunction,
* double[], double[], double[]) optimize} method. It is 0 if
* the method has not been called yet.
* </p>
* @return number of evaluations of the objective function jacobian
*/
int getJacobianEvaluations();
/** Set the convergence checker.
* @param checker object to use to check for convergence
*/
void setConvergenceChecker(VectorialConvergenceChecker checker);
/** Get the convergence checker.
* @return object used to check for convergence
*/
VectorialConvergenceChecker getConvergenceChecker();
/** Optimizes an objective function.
* <p>
* Optimization is considered to be a weighted least-squares minimization.
* The cost function to be minimized is
* ∑weight<sub>i</sub>(objective<sub>i</sub>-target<sub>i</sub>)<sup>2</sup>
* </p>
* @param f objective function
* @param target target value for the objective functions at optimum
* @param weights weight for the least squares cost computation
* @param startPoint the start point for optimization
* @return the point/value pair giving the optimal value for objective function
* @exception FunctionEvaluationException if the objective function throws one during
* the search
* @exception OptimizationException if the algorithm failed to converge
* @exception IllegalArgumentException if the start point dimension is wrong
*/
VectorialPointValuePair optimize(DifferentiableMultivariateVectorialFunction f,
double[] target, double[] weights,
double[] startPoint)
throws FunctionEvaluationException, OptimizationException, IllegalArgumentException;
}
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