NormDerivativeLem3.cpp

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00001 /*
00002  * This program is free software; you can redistribute it and/or modify
00003  * it under the terms of the GNU General Public License as published by
00004  * the Free Software Foundation; either version 3 of the License, or
00005  * (at your option) any later version.
00006  *
00007  * Written (W) 1999-2008 Soeren Sonnenburg
00008  * Copyright (C) 1999-2008 Fraunhofer Institute FIRST and Max-Planck-Society
00009  */
00010 
00011 #include "preproc/NormDerivativeLem3.h"
00012 #include "preproc/SimplePreProc.h"
00013 #include "features/Features.h"
00014 #include "features/RealFeatures.h"
00015 
00016 CNormDerivativeLem3::CNormDerivativeLem3()
00017 : CSimplePreProc<DREAL>("NormDerivativeLem3", "NDL3")
00018 {
00019 }
00020 
00021 CNormDerivativeLem3::~CNormDerivativeLem3()
00022 {
00023 }
00024 
00026 bool CNormDerivativeLem3::init(CFeatures* f)
00027 {
00028     ASSERT(f->get_feature_class()==C_SIMPLE);
00029     ASSERT(f->get_feature_type()==F_DREAL);
00030 
00031     return true;
00032 }
00033 
00035 void CNormDerivativeLem3::cleanup()
00036 {
00037 }
00038 
00040 bool CNormDerivativeLem3::load(FILE* f)
00041 {
00042     return false;
00043 }
00044 
00046 bool CNormDerivativeLem3::save(FILE* f)
00047 {
00048     return false;
00049 }
00050 
00054 DREAL* CNormDerivativeLem3::apply_to_feature_matrix(CFeatures* f)
00055 {
00056     return NULL;
00057 }
00058 
00061 DREAL* CNormDerivativeLem3::apply_to_feature_vector(DREAL* f, INT len)
00062 {
00063     return NULL;
00064 }
00065 
00066 //#warning TODO implement jahau 
00067 //#ifdef JaaHau
00068 // //this is the normalization used in jaahau
00069 //    INT o_p=1;
00070 //    double sum_p=0;
00071 //    double sum_q=0;
00072 //    //first do positive model
00073 //    for (i=0; i<pos->get_N(); i++)
00074 //    {
00075 //  featurevector[p]=exp(pos->model_derivative_p(i, x)-posx);
00076 //  sum_p=exp(pos->get_p(i))*featurevector[p++];
00077 //  featurevector[p]=exp(pos->model_derivative_q(i, x)-posx);
00078 //  sum_q=exp(pos->get_q(i))*featurevector[p++];
00079 //
00080 //  double sum_a=0;
00081 //  for (j=0; j<pos->get_N(); j++)
00082 //  {
00083 //      featurevector[p]=exp(pos->model_derivative_a(i, j, x)-posx);
00084 //      sum_a=exp(pos->get_a(i,j))*featurevector[p++];
00085 //  }
00086 //  p-=pos->get_N();
00087 //  for (j=0; j<pos->get_N(); j++)
00088 //      featurevector[p++]-=sum_a;
00089 //
00090 //  double sum_b=0;
00091 //  for (j=0; j<pos->get_M(); j++)
00092 //  {
00093 //      featurevector[p]=exp(pos->model_derivative_b(i, j, x)-posx);
00094 //      sum_b=exp(pos->get_b(i,j))*featurevector[p++];
00095 //  }
00096 //  p-=pos->get_M();
00097 //  for (j=0; j<pos->get_M(); j++)
00098 //      featurevector[p++]-=sum_b;
00099 //    }
00100 //
00101 //    o_p=p;
00102 //    p=1;
00103 //    for (i=0; i<pos->get_N(); i++)
00104 //    {
00105 //  featurevector[p++]-=sum_p;
00106 //  featurevector[p++]-=sum_q;
00107 //    }
00108 //    p=o_p;
00109 //
00110 //    for (i=0; i<neg->get_N(); i++)
00111 //    {
00112 //  featurevector[p]=-exp(neg->model_derivative_p(i, x)-negx);
00113 //  sum_p=exp(neg->get_p(i))*featurevector[p++];
00114 //  featurevector[p]=-exp(neg->model_derivative_q(i, x)-negx);
00115 //  sum_q=exp(neg->get_q(i))*featurevector[p++];
00116 //
00117 //  double sum_a=0;
00118 //  for (j=0; j<neg->get_N(); j++)
00119 //  {
00120 //      featurevector[p]=-exp(neg->model_derivative_a(i, j, x)-negx);
00121 //      sum_a=exp(neg->get_a(i,j))*featurevector[p++];
00122 //  }
00123 //  p-=neg->get_N();
00124 //  for (j=0; j<neg->get_N(); j++)
00125 //      featurevector[p++]-=sum_a;
00126 //
00127 //  double sum_b=0;
00128 //  for (j=0; j<neg->get_M(); j++)
00129 //  {
00130 //      featurevector[p]=-exp(neg->model_derivative_b(i, j, x)-negx);
00131 //      sum_b=exp(neg->get_b(i,j))*featurevector[p++];
00132 //  }
00133 //  p-=neg->get_M();
00134 //  for (j=0; j<neg->get_M(); j++)
00135 //      featurevector[p++]-=sum_b;
00136 //    }
00137 //
00138 //    p=o_p;
00139 //    for (i=0; i<neg->get_N(); i++)
00140 //    {
00141 //  featurevector[p++]-=sum_p;
00142 //  featurevector[p++]-=sum_q;
00143 //    }
00144 //#endif

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