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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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/* |
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Copyright (C) 2006, 2007 Ferdinando Ametrano |
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Copyright (C) 2007 Marco Bianchetti |
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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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|
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#include "optimization/EndCriteria.hpp" |
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#include "utils/simError.h" |
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#include <cmath> |
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#include <cstdio> |
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|
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namespace QuantLib { |
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|
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EndCriteria::EndCriteria(size_t maxIterations, |
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size_t maxStationaryStateIterations, |
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RealType rootEpsilon, |
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RealType functionEpsilon, |
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RealType gradientNormEpsilon) |
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: maxIterations_(maxIterations), |
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maxStationaryStateIterations_(maxStationaryStateIterations), |
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rootEpsilon_(rootEpsilon), |
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functionEpsilon_(functionEpsilon), |
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gradientNormEpsilon_(gradientNormEpsilon) { |
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|
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|
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// replaced the QL_REQUIRE macro with OpenMD's simError calls |
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if (maxStationaryStateIterations_ <= 1) { |
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sprintf(painCave.errMsg, |
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"maxStationaryStateIterations_ ( %lu ) " |
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"must be greater than one\n", |
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(unsigned long)maxStationaryStateIterations_); |
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painCave.isFatal = 1; |
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painCave.severity = OPENMD_ERROR; |
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simError(); |
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} |
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if (maxStationaryStateIterations_ > maxIterations_) { |
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sprintf(painCave.errMsg, |
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"maxStationaryStateIterations_ ( %lu ) " |
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"must be less than maxIterations_ ( %lu )\n", |
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(unsigned long)maxStationaryStateIterations_, |
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(unsigned long)maxIterations_); |
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painCave.isFatal = 1; |
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painCave.severity = OPENMD_ERROR; |
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simError(); |
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} |
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|
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} |
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|
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bool EndCriteria::checkMaxIterations(const size_t iteration, |
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EndCriteria::Type& ecType) const{ |
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if (iteration < maxIterations_) |
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return false; |
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ecType = MaxIterations; |
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return true; |
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} |
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|
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bool EndCriteria::checkStationaryPoint(const RealType xOld, |
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const RealType xNew, |
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size_t& statStateIterations, |
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EndCriteria::Type& ecType) const { |
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if (std::fabs(xNew-xOld) >= rootEpsilon_) { |
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statStateIterations = 0; |
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return false; |
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} |
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++statStateIterations; |
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if (statStateIterations <= maxStationaryStateIterations_) |
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return false; |
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ecType = StationaryPoint; |
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return true; |
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} |
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|
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bool EndCriteria::checkStationaryFunctionValue( |
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const RealType fxOld, |
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const RealType fxNew, |
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size_t& statStateIterations, |
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EndCriteria::Type& ecType) const { |
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if (std::fabs(fxNew-fxOld) >= functionEpsilon_) { |
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statStateIterations = 0; |
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return false; |
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} |
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++statStateIterations; |
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if (statStateIterations <= maxStationaryStateIterations_) |
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return false; |
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ecType = StationaryFunctionValue; |
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return true; |
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} |
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|
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bool EndCriteria::checkStationaryFunctionAccuracy( |
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const RealType f, |
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const bool positiveOptimization, |
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EndCriteria::Type& ecType) const { |
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if (!positiveOptimization) |
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return false; |
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if (f >= functionEpsilon_) |
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return false; |
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ecType = StationaryFunctionAccuracy; |
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return true; |
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} |
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|
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//bool EndCriteria::checkZerGradientNormValue( |
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// const RealType gNormOld, |
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// const RealType gNormNew, |
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// EndCriteria::Type& ecType) const { |
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// if (std::fabs(gNormNew-gNormOld) >= gradientNormEpsilon_) |
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// return false; |
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// ecType = StationaryGradient; |
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// return true; |
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//} |
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|
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bool EndCriteria::checkZeroGradientNorm(const RealType gradientNorm, |
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EndCriteria::Type& ecType) const { |
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if (gradientNorm >= gradientNormEpsilon_) |
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return false; |
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ecType = ZeroGradientNorm; |
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return true; |
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} |
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|
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bool EndCriteria::operator()(const size_t iteration, |
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size_t& statStateIterations, |
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const bool positiveOptimization, |
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const RealType fold, |
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const RealType, //normgold, |
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const RealType fnew, |
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const RealType normgnew, |
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EndCriteria::Type& ecType) const { |
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return |
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checkMaxIterations(iteration, ecType) || |
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checkStationaryFunctionValue(fold, fnew, statStateIterations, ecType) || |
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checkStationaryFunctionAccuracy(fnew, positiveOptimization, ecType) || |
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checkZeroGradientNorm(normgnew, ecType); |
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} |
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|
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// Inspectors |
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size_t EndCriteria::maxIterations() const { |
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return maxIterations_; |
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} |
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|
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size_t EndCriteria::maxStationaryStateIterations() const { |
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return maxStationaryStateIterations_; |
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} |
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|
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RealType EndCriteria::rootEpsilon() const { |
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return rootEpsilon_; |
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} |
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|
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RealType EndCriteria::functionEpsilon() const { |
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return functionEpsilon_; |
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} |
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|
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RealType EndCriteria::gradientNormEpsilon() const { |
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return gradientNormEpsilon_; |
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} |
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|
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std::ostream& operator<<(std::ostream& out, EndCriteria::Type ec) { |
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switch (ec) { |
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case QuantLib::EndCriteria::None: |
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return out << "None"; |
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case QuantLib::EndCriteria::MaxIterations: |
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return out << "MaxIterations"; |
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case QuantLib::EndCriteria::StationaryPoint: |
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return out << "StationaryPoint"; |
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case QuantLib::EndCriteria::StationaryFunctionValue: |
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return out << "StationaryFunctionValue"; |
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case QuantLib::EndCriteria::StationaryFunctionAccuracy: |
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return out << "StationaryFunctionAccuracy"; |
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case QuantLib::EndCriteria::ZeroGradientNorm: |
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return out << "ZeroGradientNorm"; |
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case QuantLib::EndCriteria::Unknown: |
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return out << "Unknown"; |
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default: |
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sprintf(painCave.errMsg, "unknown EndCriteria::Type ( %d )\n", |
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int(ec)); |
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painCave.isFatal = 1; |
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painCave.severity = OPENMD_ERROR; |
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simError(); |
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} |
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} |
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|
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} |
