/*
 Copyright (C) 2009 Ueli Hofstetter

 This source code is release under the BSD License.

 This file is part of JQuantLib, a free-software/open-source library
 for financial quantitative analysts and developers - http://jquantlib.org/

 JQuantLib is free software: you can redistribute it and/or modify it
 under the terms of the JQuantLib license.  You should have received a
 copy of the license along with this program; if not, please email
 . The license is also available online at
 .

 This program is distributed in the hope that it will be useful, but WITHOUT
 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 FOR A PARTICULAR PURPOSE.  See the license for more details.

 JQuantLib is based on QuantLib. http://quantlib.org/
 When applicable, the original copyright notice follows this notice.
 */
/*
 Copyright (C) 2001, 2002, 2003 Nicolas Di Cesare

 This file is part of QuantLib, a free-software/open-source library
 for financial quantitative analysts and developers - http://quantlib.org/

 QuantLib is free software: you can redistribute it and/or modify it
 under the terms of the QuantLib license.  You should have received a
 copy of the license along with this program; if not, please email
 . The license is also available online at
 .

 This program is distributed in the hope that it will be useful, but WITHOUT
 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 FOR A PARTICULAR PURPOSE.  See the license for more details.
 */

package org.jquantlib.math.optimization;

import org.jquantlib.lang.annotation.QualityAssurance;
import org.jquantlib.lang.annotation.QualityAssurance.Quality;
import org.jquantlib.lang.annotation.QualityAssurance.Version;
import org.jquantlib.math.matrixutilities.Array;

/**
 * Cost function abstract class for optimization problem.
 */
@QualityAssurance(quality=Quality.Q3_DOCUMENTATION, version=Version.V097, reviewers="Richard Gomes")
public abstract class CostFunction {

    //
    // public methods
    //

    /**
     * Method to overload to compute gradient(f), the first derivative of
     * the cost function with respect to {@latex$ x }
     */
    public void gradient(final Array  grad, final Array  x) /* @ReadOnly */ {
        final double eps = finiteDifferenceEpsilon();
        double fp, fm;
        final Array xx = x.clone();
        for (int i=0; i