1 | /*! |
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2 | \file |
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3 | \brief Mergers for combination of pdfs |
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4 | \author Vaclav Smidl. |
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5 | |
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6 | ----------------------------------- |
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7 | BDM++ - C++ library for Bayesian Decision Making under Uncertainty |
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8 | |
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9 | Using IT++ for numerical operations |
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10 | ----------------------------------- |
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11 | */ |
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12 | |
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13 | #ifndef MERGER_H |
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14 | #define MERGER_H |
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15 | |
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16 | |
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17 | #include "../estim/mixtures.h" |
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18 | #include "discrete.h" |
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19 | |
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20 | namespace bdm { |
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21 | using std::string; |
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22 | |
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23 | //!Merging methods |
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24 | enum MERGER_METHOD {ARITHMETIC = 1, GEOMETRIC = 2, LOGNORMAL = 3}; |
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25 | |
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26 | /*! |
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27 | @brief Base class for general combination of pdfs on discrete support |
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28 | |
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29 | Mixtures of Gaussian densities are used internally. Switching to other densities should be trivial. |
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30 | |
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31 | The merged pdfs are expected to be of the form: |
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32 | \f[ f(x_i|y_i), i=1..n \f] |
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33 | where the resulting merger is a density on \f$ \cup [x_i,y_i] \f$ . |
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34 | Note that all variables will be joined. |
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35 | |
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36 | As a result of this feature, each source must be extended to common support |
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37 | \f[ f(z_i|y_i,x_i) f(x_i|y_i) f(y_i) i=1..n \f] |
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38 | where \f$ z_i \f$ accumulate variables that were not in the original source. |
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39 | These extensions are calculated on-the-fly. |
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40 | |
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41 | However, these operations can not be performed in general. Hence, this class merges only sources on common support, \f$ y_i={}, z_i={}, \forall i \f$. |
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42 | For merging of more general cases, use offsprings merger_mix and merger_grid. |
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43 | */ |
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44 | |
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45 | class merger_base : public epdf { |
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46 | protected: |
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47 | //! Elements of composition |
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48 | Array<shared_ptr<pdf> > pdfs; |
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49 | |
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50 | //! Data link for each pdf in pdfs |
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51 | Array<datalink_m2e*> dls; |
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52 | |
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53 | //! Array of rvs that are not modelled by pdfs at all, \f$ z_i \f$ |
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54 | Array<RV> rvzs; |
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55 | |
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56 | //! Data Links for extension \f$ f(z_i|x_i,y_i) \f$ |
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57 | Array<datalink_m2e*> zdls; |
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58 | |
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59 | //! number of support points |
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60 | int Npoints; |
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61 | |
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62 | //! number of sources |
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63 | int Nsources; |
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64 | |
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65 | //! switch of the methoh used for merging |
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66 | MERGER_METHOD METHOD; |
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67 | //! Default for METHOD |
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68 | static const MERGER_METHOD DFLT_METHOD; |
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69 | |
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70 | //!Prior on the log-normal merging model |
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71 | double beta; |
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72 | //! default for beta |
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73 | static const double DFLT_beta; |
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74 | |
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75 | //! Projection to empirical density (could also be piece-wise linear) |
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76 | eEmp eSmp; |
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77 | |
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78 | //! debug or not debug |
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79 | bool DBG; |
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80 | |
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81 | //! debugging file |
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82 | it_file* dbg_file; |
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83 | public: |
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84 | //! \name Constructors |
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85 | //! @{ |
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86 | |
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87 | //! Default constructor |
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88 | merger_base () : Npoints ( 0 ), Nsources ( 0 ), DBG ( false ), dbg_file ( 0 ) { |
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89 | } |
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90 | |
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91 | //!Constructor from sources |
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92 | merger_base ( const Array<shared_ptr<pdf> > &S ); |
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93 | |
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94 | //! Function setting the main internal structures |
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95 | void set_sources ( const Array<shared_ptr<pdf> > &Sources ); |
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96 | |
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97 | //! Set support points from rectangular grid |
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98 | void set_support ( rectangular_support &Sup ); |
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99 | |
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100 | //! Set support points from dicrete grid |
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101 | void set_support ( discrete_support &Sup ) { |
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102 | Npoints = Sup.points(); |
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103 | eSmp.set_parameters ( Sup._Spoints() ); |
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104 | eSmp.validate(); |
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105 | } |
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106 | |
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107 | |
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108 | //! set debug file |
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109 | void set_debug_file ( const string fname ) { |
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110 | if ( DBG ) delete dbg_file; |
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111 | dbg_file = new it_file ( fname ); |
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112 | DBG = ( dbg_file != 0 ); |
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113 | } |
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114 | |
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115 | //! Set internal parameters used in approximation |
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116 | void set_method ( MERGER_METHOD MTH = DFLT_METHOD, double beta0 = DFLT_beta ) { |
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117 | METHOD = MTH; |
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118 | beta = beta0; |
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119 | } |
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120 | //! Set support points from a pdf by drawing N samples |
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121 | void set_support ( const epdf &overall, int N ) { |
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122 | eSmp.set_statistics ( overall, N ); |
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123 | Npoints = N; |
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124 | } |
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125 | |
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126 | //! Destructor |
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127 | virtual ~merger_base() { |
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128 | for ( int i = 0; i < Nsources; i++ ) { |
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129 | delete dls ( i ); |
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130 | delete zdls ( i ); |
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131 | } |
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132 | if ( DBG ) delete dbg_file; |
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133 | }; |
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134 | //!@} |
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135 | |
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136 | //! \name Mathematical operations |
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137 | //!@{ |
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138 | |
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139 | //!Merge given sources in given points |
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140 | virtual void merge (); |
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141 | |
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142 | //! Merge log-likelihood values in points using method specified by parameter METHOD |
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143 | vec merge_points ( mat &lW ); |
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144 | |
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145 | |
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146 | //! sample from merged density |
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147 | //! weight w is a |
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148 | vec mean() const; |
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149 | |
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150 | mat covariance() const; |
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151 | |
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152 | vec variance() const; |
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153 | |
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154 | //! Compute log-probability of argument \c val |
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155 | virtual double evallog ( const vec &val ) const NOT_IMPLEMENTED(0); |
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156 | |
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157 | //! Returns a sample, \f$ x \f$ from density \f$ f_x()\f$ |
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158 | virtual vec sample() const NOT_IMPLEMENTED(0); |
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159 | |
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160 | //!@} |
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161 | |
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162 | //! \name Access to attributes |
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163 | //! @{ |
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164 | |
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165 | //! Access function |
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166 | eEmp& _Smp() { |
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167 | return eSmp; |
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168 | } |
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169 | |
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170 | //! load from setting |
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171 | void from_setting ( const Setting& set ); |
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172 | |
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173 | void to_setting (Setting &set) const ; |
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174 | |
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175 | void validate() ; |
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176 | //!@} |
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177 | }; |
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178 | UIREGISTER ( merger_base ); |
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179 | SHAREDPTR ( merger_base ); |
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180 | |
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181 | //! Merger using importance sampling with mixture proposal density |
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182 | class merger_mix : public merger_base { |
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183 | protected: |
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184 | //!Internal mixture of EF models |
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185 | MixEF Mix; |
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186 | //!Number of components in a mixture |
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187 | int Ncoms; |
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188 | //! coefficient of resampling [0,1] |
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189 | double effss_coef; |
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190 | //! stop after niter iterations |
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191 | int stop_niter; |
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192 | |
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193 | //! default value for Ncoms |
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194 | static const int DFLT_Ncoms; |
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195 | //! default value for efss_coef; |
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196 | static const double DFLT_effss_coef; |
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197 | |
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198 | public: |
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199 | //!\name Constructors |
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200 | //!@{ |
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201 | merger_mix () : Ncoms ( 0 ), effss_coef ( 0 ), stop_niter ( 0 ) { } |
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202 | |
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203 | merger_mix ( const Array<shared_ptr<pdf> > &S ) : |
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204 | Ncoms ( 0 ), effss_coef ( 0 ), stop_niter ( 0 ) { |
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205 | set_sources ( S ); |
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206 | } |
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207 | |
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208 | //! Set sources and prepare all internal structures |
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209 | void set_sources ( const Array<shared_ptr<pdf> > &S ) { |
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210 | merger_base::set_sources ( S ); |
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211 | //Nsources = S.length(); |
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212 | } |
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213 | |
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214 | //! Set internal parameters used in approximation |
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215 | void set_parameters ( int Ncoms0 = DFLT_Ncoms, double effss_coef0 = DFLT_effss_coef ) { |
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216 | Ncoms = Ncoms0; |
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217 | effss_coef = effss_coef0; |
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218 | } |
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219 | //!@} |
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220 | |
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221 | //! \name Mathematical operations |
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222 | //!@{ |
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223 | |
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224 | //!Merge values using mixture approximation |
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225 | void merge (); |
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226 | |
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227 | //! sample from the approximating mixture |
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228 | vec sample () const { |
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229 | return Mix.posterior().sample(); |
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230 | } |
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231 | //! loglikelihood computed on mixture models |
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232 | double evallog ( const vec &yt ) const { |
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233 | vec dtf = ones ( yt.length() + 1 ); |
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234 | dtf.set_subvector ( 0, yt ); |
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235 | return Mix.logpred ( dtf ); |
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236 | } |
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237 | //!@} |
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238 | |
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239 | //!\name Access functions |
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240 | //!@{ |
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241 | //! Access function |
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242 | MixEF& _Mix() { |
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243 | return Mix; |
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244 | } |
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245 | //! Access function |
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246 | emix* proposal() { |
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247 | emix* tmp = Mix.epredictor(); |
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248 | tmp->set_rv ( rv ); |
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249 | return tmp; |
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250 | } |
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251 | //! from_settings |
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252 | void from_setting ( const Setting& set ); |
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253 | void to_setting (Setting &set) const; |
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254 | void validate(); |
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255 | |
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256 | //! @} |
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257 | |
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258 | }; |
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259 | UIREGISTER ( merger_mix ); |
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260 | SHAREDPTR ( merger_mix ); |
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261 | |
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262 | } |
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263 | |
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264 | #endif // MER_H |
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