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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */ |
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/* |
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Copyright (C) 2001, 2002, 2003 Nicolas Di Césaré |
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|
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This file is part of QuantLib, a free-software/open-source library |
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for financial quantitative analysts and developers - http://quantlib.org/ |
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|
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QuantLib is free software: you can redistribute it and/or modify it |
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under the terms of the QuantLib license. You should have received a |
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copy of the license along with this program; if not, please email |
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<quantlib-dev@lists.sf.net>. The license is also available online at |
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<http://quantlib.org/license.shtml>. |
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|
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This program is distributed in the hope that it will be useful, but WITHOUT |
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ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
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FOR A PARTICULAR PURPOSE. See the license for more details. |
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*/ |
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#include "optimization/Armijo.hpp" |
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#include "optimization/Method.hpp" |
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#include "optimization/Problem.hpp" |
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|
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namespace QuantLib { |
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|
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RealType ArmijoLineSearch::operator()(Problem& P, |
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EndCriteria::Type& ecType, |
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const EndCriteria& endCriteria, |
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const RealType t_ini) |
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{ |
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//OptimizationMethod& method = P.method(); |
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Constraint& constraint = P.constraint(); |
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succeed_=true; |
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bool maxIter = false; |
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RealType t = t_ini; |
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|
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|
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RealType q0 = P.functionValue(); |
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RealType qp0 = P.gradientNormValue(); |
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|
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qt_ = q0; |
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qpt_ = (gradient_.empty()) ? qp0 : -P.DotProduct(gradient_,searchDirection_); |
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|
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// Initialize gradient |
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gradient_ = DynamicVector<RealType>(P.currentValue().size()); |
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// Compute new point |
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xtd_ = P.currentValue(); |
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t = update(xtd_, searchDirection_, t, constraint); |
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// Compute function value at the new point |
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qt_ = P.value (xtd_); |
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|
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// Enter in the loop if the criterion is not satisfied |
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if ((qt_-q0) > -alpha_*t*qpt_) { |
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RealType qtold; |
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size_t loopNumber = 0; |
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do { |
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loopNumber++; |
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// Decrease step |
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t *= beta_; |
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// Store old value of the function |
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qtold = qt_; |
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// New point value |
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xtd_ = P.currentValue(); |
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t = update(xtd_, searchDirection_, t, constraint); |
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|
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// Compute function value at the new point |
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qt_ = P.value (xtd_); |
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P.gradient (gradient_, xtd_); |
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// and it squared norm |
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maxIter = endCriteria.checkMaxIterations(loopNumber, ecType); |
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} while ( |
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(((qt_ - q0) > (-alpha_ * t * qpt_)) || |
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((qtold - q0) <= (-alpha_ * t * qpt_ / beta_))) && |
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(!maxIter)); |
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} |
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|
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if (maxIter) |
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succeed_ = false; |
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// Compute new gradient |
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P.gradient(gradient_, xtd_); |
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// and it squared norm |
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qpt_ = P.computeGradientNormValue(gradient_); |
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//qpt_ = P.DotProduct(gradient_, gradient_); |
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|
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// Return new step value |
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return t; |
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} |
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|
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} |
