problem.hpp

/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
 
/*
 Copyright (C) 2007 Ferdinando Ametrano
 Copyright (C) 2007 François du Vignaud
 Copyright (C) 2001, 2002, 2003 Nicolas Di Césaré
 
 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
 <quantlib-dev@lists.sf.net>. The license is also available online at
 <http://quantlib.org/license.shtml>.
 
 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.
*/
 
#ifndef quantlib_optimization_problem_h
#define quantlib_optimization_problem_h
 
#include <ql/math/optimization/constraint.hpp>
#include <ql/math/optimization/costfunction.hpp>
#include <ql/math/optimization/method.hpp>
#include <utility>
 
namespace QuantLib {
 
 
    class Problem {
      public:
        Problem(CostFunction& costFunction, Constraint& constraint, Array initialValue = Array())
        : costFunction_(costFunction), constraint_(constraint),
          currentValue_(std::move(initialValue)) {
            QL_REQUIRE(!constraint.empty(), "empty constraint given");
        }
 
        void reset();
 
        Real value(const Array& x);
 
        Array values(const Array& x);
 
        //  evaluation counter
        void gradient(Array& grad_f,
                      const Array& x);
 
        Real valueAndGradient(Array& grad_f,
                              const Array& x);
 
        Constraint& constraint() const { return constraint_; }
 
        CostFunction& costFunction() const { return costFunction_; }
 
        void setCurrentValue(const Array& currentValue) {
            currentValue_=currentValue;
        }
 
        const Array& currentValue() const { return currentValue_; }
 
        void setFunctionValue(Real functionValue) {
            functionValue_=functionValue;
        }
 
        Real functionValue() const { return functionValue_; }
 
        void setGradientNormValue(Real squaredNorm) {
            squaredNorm_=squaredNorm;
        }
        Real gradientNormValue() const { return squaredNorm_; }
 
        Integer functionEvaluation() const { return functionEvaluation_; }
 
        Integer gradientEvaluation() const { return gradientEvaluation_; }
 
      protected:
        CostFunction& costFunction_;
        Constraint& constraint_;
        Array currentValue_;
        Real functionValue_, squaredNorm_;
        Integer functionEvaluation_, gradientEvaluation_;
    };
 
    // inline definitions
    inline Real Problem::value(const Array& x) {
        ++functionEvaluation_;
        return costFunction_.value(x);
    }
 
    inline Array Problem::values(const Array& x) {
        ++functionEvaluation_;
        return costFunction_.values(x);
    }
 
    inline void Problem::gradient(Array& grad_f,
                                  const Array& x) {
        ++gradientEvaluation_;
        costFunction_.gradient(grad_f, x);
    }
 
    inline Real Problem::valueAndGradient(Array& grad_f,
                                          const Array& x) {
        ++functionEvaluation_;
        ++gradientEvaluation_;
        return costFunction_.valueAndGradient(grad_f, x);
    }
 
    inline void Problem::reset() {
        functionEvaluation_ = gradientEvaluation_ = 0;
        functionValue_ = squaredNorm_ = Null<Real>();
    }
 
}
 
#endif