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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2001, 2002, 2003 Nicolas Di Csar
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.
*/
#include <ql/math/optimization/steepestdescent.hpp>
#include <ql/math/optimization/problem.hpp>
#include <ql/math/optimization/linesearch.hpp>
namespace QuantLib {
EndCriteria::Type SteepestDescent::minimize(Problem& P,
const EndCriteria& endCriteria) {
EndCriteria::Type ecType = EndCriteria::None;
P.reset();
Array x_ = P.currentValue();
Size iterationNumber_=0, stationaryStateIterationNumber_=0;
lineSearch_->searchDirection() = Array(x_.size());
bool end;
// function and squared norm of gradient values;
Real normdiff;
// classical initial value for line-search step
Real t = 1.0;
// Set gold at the size of the optimization problem search direction
Array gold(lineSearch_->searchDirection().size());
Array gdiff(lineSearch_->searchDirection().size());
P.setFunctionValue(P.valueAndGradient(gold, x_));
lineSearch_->searchDirection() = -gold;
P.setGradientNormValue(DotProduct(gold, gold));
normdiff = std::sqrt(P.gradientNormValue());
do {
// Linesearch
t = (*lineSearch_)(P, ecType, endCriteria, t);
QL_REQUIRE(lineSearch_->succeed(), "line-search failed!");
// End criteria
end = endCriteria(iterationNumber_,
stationaryStateIterationNumber_,
true, //FIXME: it should be in the problem
P.functionValue(),
std::sqrt(P.gradientNormValue()),
lineSearch_->lastFunctionValue(),
std::sqrt(lineSearch_->lastGradientNorm2()),
ecType
// FIXME: it's never been used! ???
// , normdiff
);
// Updates
// New point
x_ = lineSearch_->lastX();
// New function value
P.setFunctionValue(lineSearch_->lastFunctionValue());
// New gradient and search direction vectors
gdiff = gold - lineSearch_->lastGradient();
normdiff = std::sqrt(DotProduct (gdiff, gdiff));
gold = lineSearch_->lastGradient();
lineSearch_->searchDirection() = -gold;
// New gradient squared norm
P.setGradientNormValue(lineSearch_->lastGradientNorm2());
// Increase interation number
++iterationNumber_;
} while (end == false);
P.setCurrentValue(x_);
return ecType;
}
}
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