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>


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:	1741
Committed:	Tue Jun 5 18:02:44 2012 UTC (12 years, 10 months ago) by gezelter
File size:	7604 byte(s)
Log Message:	Adding initial import of optimization library
#	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
26
27
28			namespace QuantLib {
29
30			EndCriteria::EndCriteria(size_t maxIterations,
31			size_t maxStationaryStateIterations,
32			RealType rootEpsilon,
33			RealType functionEpsilon,
34			RealType gradientNormEpsilon)
35			: maxIterations_(maxIterations),
36			maxStationaryStateIterations_(maxStationaryStateIterations),
37			rootEpsilon_(rootEpsilon),
38			functionEpsilon_(functionEpsilon),
39			gradientNormEpsilon_(gradientNormEpsilon) {
40
41
42			// replaced the QL_REQUIRE macro with OpenMD's simError calls
43			if (maxStationaryStateIterations_ <= 1) {
44			sprintf(painCave.errMsg,
45			"maxStationaryStateIterations_ ( %lu ) "
46			"must be greater than one\n",
47			(unsigned long)maxStationaryStateIterations_);
48			painCave.isFatal = 1;
49			painCave.severity = OPENMD_ERROR;
50			simError();
51			}
52			if (maxStationaryStateIterations_ > maxIterations_) {
53			sprintf(painCave.errMsg,
54			"maxStationaryStateIterations_ ( %lu ) "
55			"must be less than maxIterations_ ( %lu )\n",
56			(unsigned long)maxStationaryStateIterations_,
57			(unsigned long)maxIterations_);
58			painCave.isFatal = 1;
59			painCave.severity = OPENMD_ERROR;
60			simError();
61			}
62
63			}
64
65			bool EndCriteria::checkMaxIterations(const size_t iteration,
66			EndCriteria::Type& ecType) const{
67			if (iteration < maxIterations_)
68			return false;
69			ecType = MaxIterations;
70			return true;
71			}
72
73			bool EndCriteria::checkStationaryPoint(const RealType xOld,
74			const RealType xNew,
75			size_t& statStateIterations,
76			EndCriteria::Type& ecType) const {
77			if (std::fabs(xNew-xOld) >= rootEpsilon_) {
78			statStateIterations = 0;
79			return false;
80			}
81			++statStateIterations;
82			if (statStateIterations <= maxStationaryStateIterations_)
83			return false;
84			ecType = StationaryPoint;
85			return true;
86			}
87
88			bool EndCriteria::checkStationaryFunctionValue(
89			const RealType fxOld,
90			const RealType fxNew,
91			size_t& statStateIterations,
92			EndCriteria::Type& ecType) const {
93			if (std::fabs(fxNew-fxOld) >= functionEpsilon_) {
94			statStateIterations = 0;
95			return false;
96			}
97			++statStateIterations;
98			if (statStateIterations <= maxStationaryStateIterations_)
99			return false;
100			ecType = StationaryFunctionValue;
101			return true;
102			}
103
104			bool EndCriteria::checkStationaryFunctionAccuracy(
105			const RealType f,
106			const bool positiveOptimization,
107			EndCriteria::Type& ecType) const {
108			if (!positiveOptimization)
109			return false;
110			if (f >= functionEpsilon_)
111			return false;
112			ecType = StationaryFunctionAccuracy;
113			return true;
114			}
115
116			//bool EndCriteria::checkZerGradientNormValue(
117			// const RealType gNormOld,
118			// const RealType gNormNew,
119			// EndCriteria::Type& ecType) const {
120			// if (std::fabs(gNormNew-gNormOld) >= gradientNormEpsilon_)
121			// return false;
122			// ecType = StationaryGradient;
123			// return true;
124			//}
125
126			bool EndCriteria::checkZeroGradientNorm(const RealType gradientNorm,
127			EndCriteria::Type& ecType) const {
128			if (gradientNorm >= gradientNormEpsilon_)
129			return false;
130			ecType = ZeroGradientNorm;
131			return true;
132			}
133
134			bool EndCriteria::operator()(const size_t iteration,
135			size_t& statStateIterations,
136			const bool positiveOptimization,
137			const RealType fold,
138			const RealType, //normgold,
139			const RealType fnew,
140			const RealType normgnew,
141			EndCriteria::Type& ecType) const {
142			return
143			checkMaxIterations(iteration, ecType) \|\|
144			checkStationaryFunctionValue(fold, fnew, statStateIterations, ecType) \|\|
145			checkStationaryFunctionAccuracy(fnew, positiveOptimization, ecType) \|\|
146			checkZeroGradientNorm(normgnew, ecType);
147			}
148
149			// Inspectors
150			size_t EndCriteria::maxIterations() const {
151			return maxIterations_;
152			}
153
154			size_t EndCriteria::maxStationaryStateIterations() const {
155			return maxStationaryStateIterations_;
156			}
157
158			RealType EndCriteria::rootEpsilon() const {
159			return rootEpsilon_;
160			}
161
162			RealType EndCriteria::functionEpsilon() const {
163			return functionEpsilon_;
164			}
165
166			RealType EndCriteria::gradientNormEpsilon() const {
167			return gradientNormEpsilon_;
168			}
169
170			std::ostream& operator<<(std::ostream& out, EndCriteria::Type ec) {
171			switch (ec) {
172			case QuantLib::EndCriteria::None:
173			return out << "None";
174			case QuantLib::EndCriteria::MaxIterations:
175			return out << "MaxIterations";
176			case QuantLib::EndCriteria::StationaryPoint:
177			return out << "StationaryPoint";
178			case QuantLib::EndCriteria::StationaryFunctionValue:
179			return out << "StationaryFunctionValue";
180			case QuantLib::EndCriteria::StationaryFunctionAccuracy:
181			return out << "StationaryFunctionAccuracy";
182			case QuantLib::EndCriteria::ZeroGradientNorm:
183			return out << "ZeroGradientNorm";
184			case QuantLib::EndCriteria::Unknown:
185			return out << "Unknown";
186			default:
187			sprintf(painCave.errMsg, "unknown EndCriteria::Type ( %d )\n",
188			int(ec));
189			painCave.isFatal = 1;
190			painCave.severity = OPENMD_ERROR;
191			simError();
192			}
193			}
194
195			}