Image Component Library (ICL)
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00001 /******************************************************************** 00002 ** Image Component Library (ICL) ** 00003 ** ** 00004 ** Copyright (C) 2006-2013 CITEC, University of Bielefeld ** 00005 ** Neuroinformatics Group ** 00006 ** Website: www.iclcv.org and ** 00007 ** http://opensource.cit-ec.de/projects/icl ** 00008 ** ** 00009 ** File : ICLMath/src/ICLMath/StochasticOptimizer.h ** 00010 ** Module : ICLMath ** 00011 ** Authors: Christof Elbrechter ** 00012 ** ** 00013 ** ** 00014 ** GNU LESSER GENERAL PUBLIC LICENSE ** 00015 ** This file may be used under the terms of the GNU Lesser General ** 00016 ** Public License version 3.0 as published by the ** 00017 ** ** 00018 ** Free Software Foundation and appearing in the file LICENSE.LGPL ** 00019 ** included in the packaging of this file. Please review the ** 00020 ** following information to ensure the license requirements will ** 00021 ** be met: http://www.gnu.org/licenses/lgpl-3.0.txt ** 00022 ** ** 00023 ** The development of this software was supported by the ** 00024 ** Excellence Cluster EXC 277 Cognitive Interaction Technology. ** 00025 ** The Excellence Cluster EXC 277 is a grant of the Deutsche ** 00026 ** Forschungsgemeinschaft (DFG) in the context of the German ** 00027 ** Excellence Initiative. ** 00028 ** ** 00029 ********************************************************************/ 00030 00031 #pragma once 00032 00033 #include <ICLUtils/CompatMacros.h> 00034 00035 namespace icl{ 00036 namespace math{ 00037 00039 template<class T> 00040 struct StochasticOptimizerResult{ 00042 StochasticOptimizerResult(const T *data=0,T error=0, T startError=0, int steps=0); 00043 const T *data; 00044 T error; 00045 T startError; 00046 int steps; 00047 }; 00048 00050 00062 template<class T=float> 00063 class ICLMath_IMP StochasticOptimizer { 00064 public: 00066 typedef StochasticOptimizerResult<T> Result; 00067 00069 StochasticOptimizer(int dataDim); 00070 00072 Result optimize(int maxTimeSteps){ 00073 return optimize(-1,maxTimeSteps); 00074 } 00075 00077 Result optimize(T minError, int maxSteps); 00078 00079 protected: 00081 00084 virtual T *getData() = 0; 00085 00087 00088 virtual T getError(const T *data)=0; 00089 00091 00093 virtual const T *getNoise(int currentTime, int endTime)=0; 00094 00096 00097 virtual void reinitialize() = 0; 00098 00100 virtual void notifyProgress(int t, int numSteps, int startError, 00101 int currBestError, int currError,const T *data, int dataDim); 00102 00103 private: 00105 int m_dataDim; 00106 }; 00107 00108 } // namespace math 00109 } 00110