src/optimization/EndCriteria.cpp

/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */

/*
 Copyright (C) 2006, 2007 Ferdinando Ametrano
 Copyright (C) 2007 Marco Bianchetti
 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.
*/

#include "optimization/EndCriteria.hpp"
#include "utils/simError.h"
#include <cmath>
#include <cstdio>

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

}
Revision:	1788
Committed:	Wed Aug 29 20:17:07 2012 UTC (13 years, 1 month ago) by gezelter
File size:	7620 byte(s)
Log Message:	Fixed a bug in ForceManager and a compilation issue for cygwin
#	User	Rev	Content
1	gezelter	1741	/* -- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -- */
2
3			/*
4			Copyright (C) 2006, 2007 Ferdinando Ametrano
5			Copyright (C) 2007 Marco Bianchetti
6			Copyright (C) 2001, 2002, 2003 Nicolas Di Césaré
7
8			This file is part of QuantLib, a free-software/open-source library
9			for financial quantitative analysts and developers - http://quantlib.org/
10
11			QuantLib is free software: you can redistribute it and/or modify it
12			under the terms of the QuantLib license. You should have received a
13			copy of the license along with this program; if not, please email
14			<quantlib-dev@lists.sf.net>. The license is also available online at
15			<http://quantlib.org/license.shtml>.
16
17			This program is distributed in the hope that it will be useful, but WITHOUT
18			ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
19			FOR A PARTICULAR PURPOSE. See the license for more details.
20			*/
21
22			#include "optimization/EndCriteria.hpp"
23			#include "utils/simError.h"
24			#include <cmath>
25	gezelter	1788	#include <cstdio>
26	gezelter	1741
27			namespace QuantLib {
28
29			EndCriteria::EndCriteria(size_t maxIterations,
30			size_t maxStationaryStateIterations,
31			RealType rootEpsilon,
32			RealType functionEpsilon,
33			RealType gradientNormEpsilon)
34			: maxIterations_(maxIterations),
35			maxStationaryStateIterations_(maxStationaryStateIterations),
36			rootEpsilon_(rootEpsilon),
37			functionEpsilon_(functionEpsilon),
38			gradientNormEpsilon_(gradientNormEpsilon) {
39
40
41			// replaced the QL_REQUIRE macro with OpenMD's simError calls
42			if (maxStationaryStateIterations_ <= 1) {
43			sprintf(painCave.errMsg,
44			"maxStationaryStateIterations_ ( %lu ) "
45			"must be greater than one\n",
46			(unsigned long)maxStationaryStateIterations_);
47			painCave.isFatal = 1;
48			painCave.severity = OPENMD_ERROR;
49			simError();
50			}
51			if (maxStationaryStateIterations_ > maxIterations_) {
52			sprintf(painCave.errMsg,
53			"maxStationaryStateIterations_ ( %lu ) "
54			"must be less than maxIterations_ ( %lu )\n",
55			(unsigned long)maxStationaryStateIterations_,
56			(unsigned long)maxIterations_);
57			painCave.isFatal = 1;
58			painCave.severity = OPENMD_ERROR;
59			simError();
60			}
61
62			}
63
64			bool EndCriteria::checkMaxIterations(const size_t iteration,
65			EndCriteria::Type& ecType) const{
66			if (iteration < maxIterations_)
67			return false;
68			ecType = MaxIterations;
69			return true;
70			}
71
72			bool EndCriteria::checkStationaryPoint(const RealType xOld,
73			const RealType xNew,
74			size_t& statStateIterations,
75			EndCriteria::Type& ecType) const {
76			if (std::fabs(xNew-xOld) >= rootEpsilon_) {
77			statStateIterations = 0;
78			return false;
79			}
80			++statStateIterations;
81			if (statStateIterations <= maxStationaryStateIterations_)
82			return false;
83			ecType = StationaryPoint;
84			return true;
85			}
86
87			bool EndCriteria::checkStationaryFunctionValue(
88			const RealType fxOld,
89			const RealType fxNew,
90			size_t& statStateIterations,
91			EndCriteria::Type& ecType) const {
92			if (std::fabs(fxNew-fxOld) >= functionEpsilon_) {
93			statStateIterations = 0;
94			return false;
95			}
96			++statStateIterations;
97			if (statStateIterations <= maxStationaryStateIterations_)
98			return false;
99			ecType = StationaryFunctionValue;
100			return true;
101			}
102
103			bool EndCriteria::checkStationaryFunctionAccuracy(
104			const RealType f,
105			const bool positiveOptimization,
106			EndCriteria::Type& ecType) const {
107			if (!positiveOptimization)
108			return false;
109			if (f >= functionEpsilon_)
110			return false;
111			ecType = StationaryFunctionAccuracy;
112			return true;
113			}
114
115			//bool EndCriteria::checkZerGradientNormValue(
116			// const RealType gNormOld,
117			// const RealType gNormNew,
118			// EndCriteria::Type& ecType) const {
119			// if (std::fabs(gNormNew-gNormOld) >= gradientNormEpsilon_)
120			// return false;
121			// ecType = StationaryGradient;
122			// return true;
123			//}
124
125			bool EndCriteria::checkZeroGradientNorm(const RealType gradientNorm,
126			EndCriteria::Type& ecType) const {
127			if (gradientNorm >= gradientNormEpsilon_)
128			return false;
129			ecType = ZeroGradientNorm;
130			return true;
131			}
132
133			bool EndCriteria::operator()(const size_t iteration,
134			size_t& statStateIterations,
135			const bool positiveOptimization,
136			const RealType fold,
137			const RealType, //normgold,
138			const RealType fnew,
139			const RealType normgnew,
140			EndCriteria::Type& ecType) const {
141			return
142			checkMaxIterations(iteration, ecType) \|\|
143			checkStationaryFunctionValue(fold, fnew, statStateIterations, ecType) \|\|
144			checkStationaryFunctionAccuracy(fnew, positiveOptimization, ecType) \|\|
145			checkZeroGradientNorm(normgnew, ecType);
146			}
147
148			// Inspectors
149			size_t EndCriteria::maxIterations() const {
150			return maxIterations_;
151			}
152
153			size_t EndCriteria::maxStationaryStateIterations() const {
154			return maxStationaryStateIterations_;
155			}
156
157			RealType EndCriteria::rootEpsilon() const {
158			return rootEpsilon_;
159			}
160
161			RealType EndCriteria::functionEpsilon() const {
162			return functionEpsilon_;
163			}
164
165			RealType EndCriteria::gradientNormEpsilon() const {
166			return gradientNormEpsilon_;
167			}
168
169			std::ostream& operator<<(std::ostream& out, EndCriteria::Type ec) {
170			switch (ec) {
171			case QuantLib::EndCriteria::None:
172			return out << "None";
173			case QuantLib::EndCriteria::MaxIterations:
174			return out << "MaxIterations";
175			case QuantLib::EndCriteria::StationaryPoint:
176			return out << "StationaryPoint";
177			case QuantLib::EndCriteria::StationaryFunctionValue:
178			return out << "StationaryFunctionValue";
179			case QuantLib::EndCriteria::StationaryFunctionAccuracy:
180			return out << "StationaryFunctionAccuracy";
181			case QuantLib::EndCriteria::ZeroGradientNorm:
182			return out << "ZeroGradientNorm";
183			case QuantLib::EndCriteria::Unknown:
184			return out << "Unknown";
185			default:
186			sprintf(painCave.errMsg, "unknown EndCriteria::Type ( %d )\n",
187			int(ec));
188			painCave.isFatal = 1;
189			painCave.severity = OPENMD_ERROR;
190			simError();
191			}
192			}
193
194			}