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/LeastSquareModelFitting.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.GPL ** 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 <ICLMath/DynMatrix.h> 00034 00035 namespace icl{ 00036 namespace math{ 00037 00039 00131 template<class T, class DataPoint> 00132 class LeastSquareModelFitting{ 00133 public: 00135 00136 typedef Function<void,const DataPoint&,T*> DesignMatrixGen; 00137 00139 typedef std::vector<T> Model; 00140 00141 private: 00143 int m_modelDim; 00144 00146 DesignMatrixGen m_gen; 00147 00149 DynMatrix<T> m_D, m_S, m_Evecs, m_Evals; 00150 00152 SmartPtr<DynMatrix<T> >m_C; 00153 00155 Model m_model; 00156 00157 public: 00158 00160 LeastSquareModelFitting(){} 00161 00163 LeastSquareModelFitting(int modelDim, DesignMatrixGen gen, 00164 DynMatrix<T> *constraintMatrix=0): 00165 m_modelDim(modelDim),m_gen(gen),m_S(modelDim,modelDim), 00166 m_C(constraintMatrix),m_model(modelDim){ 00167 00168 } 00169 00171 00172 icl64f getError(const Model &model,const DataPoint &p){ 00173 std::vector<T> d(m_modelDim); 00174 m_gen(p,d.data()); 00175 icl64f e = 0; 00176 for(int i=0;i<m_modelDim;++i) e += d[i] * model[i]; 00177 return fabs(e); 00178 } 00179 00181 00184 Model fit(const std::vector<DataPoint> &points){ 00185 const int M = m_modelDim; 00186 const int N = (int)points.size(); 00187 00188 m_D.setBounds(M,N); 00189 00191 for(int i=0;i<N;i++){ 00192 m_gen(points[i],m_D.row_begin(i)); 00193 } 00194 00196 m_D.transp().mult(m_D,m_S); 00197 00198 00199 00200 DynMatrix<T> Si; 00201 try{ 00202 Si = m_C ? m_S.inv()* (*m_C) : m_S.inv(); 00203 }catch(SingularMatrixException &ex){ 00204 Si = m_C ? m_S.pinv(true)* (*m_C) : m_S.pinv(true); 00205 } 00206 00207 try{ 00208 Si.eigen(m_Evecs, m_Evals); 00210 std::copy(m_Evecs.col_begin(0), m_Evecs.col_end(0), m_model.begin()); 00211 }catch(ICLException &e){ 00212 std::fill(m_model.begin(),m_model.end(),Range<T>::limits().maxVal); 00213 } 00214 00215 return m_model; 00216 } 00217 }; 00218 } // namespace math 00219 } 00220 00221