141 }
142 **r e t u r n t r u e** ; 143 }
144 145 **p r o t e c t e d i n t** drawTable_sampler **( ) {** 146 i f ( __updated ) i f ( ! setTables_sampler ( ) ) **r e t u r n** −1; 147 **d oub l e** x=rng . nextDouble **( ) ;**
148 **i n t** i=jumpTable_Sampler [ ( i n t ) ( jumpTable_Sampler . length∗x **) ] ;** 149 **w h i l e** ( x>=c u m u l a t i v e D is tr ibu ti on _Sa mp le r [ i ] ) i++;
150 **r e t u r n** i ;
151 }
152 153 **p r o t e c t e d i n t** drawTable_mixer **( ) {**
154 **d oub l e** x=rng . nextDouble **( ) ;**
155 **i n t** i=jumpTable_Mixer [ ( i n t ) ( jumpTable_Mixer . length∗x **) ] ;** 156 **w h i l e** ( x>=c u m u l a t i v e D ist ri but io n_ Mix er [ i ] ) i++;
157 **r e t u r n** i ;
158 }
159 160 161 **// / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / :**
162 **// p u b l i c p a r t**
163 **// /////////////** 164 165 @Override 166 **p u b l i c v o id** update_notification ( ) { **// c a l l e d ea ch t im e a chang e i s done** 167 **sup e r** . update_notification **( ) ;**
168 __updated**=t r u e** ;
169 }
170 171 **p u b l i c d oub l e** learnFrom ( ArrayList <Assignment <Prop>> weightedSamples ) {
172 **i n t** i , nbSamples ;
173 **d oub l e** normalizer , aValue , Z ; 174 Prop aProposition ;
175 Assignment <Prop> anAssignment ;
176 nbSamples=weightedSamples . size **( ) ;**
177 Z=( normalizer **=0 .) ;**
178 179 f o r ( i=0;i<nbSamples ; i**++) {**
180 anAssignment=weightedSamples . get ( i ) ;
181 aValue=anAssignment . value ; 182 i f ( aValue **<=0) {** 183 System . err . println ( **" E r r o r : : "+t h i s** . getClass **( ) .** getName **( ) +**
184 " . l earnFrom ( A r r ay L i s t<Ass ignment<Prop>>)" ) ;
185 System . err . println ( " N e g a t i v e w e i gh t e n c oun t e r e d " ) ;
186 System . exit **( 0 ) ;**
187 }
188 aProposition = anAssignment . attribute ;
189 i f ( theZero**==n u l l** ) theZero = aProposition . instanceNsize **( ) .** zero **( ) ;**
190 i f ( aProposition . compareTo ( theZero **)==0)** Z+=aValue ;
191 **e l s e** normalizer+=aValue ;
192 }
193 clear **( ) ;**
194 f o r ( i=0;i<nbSamples ; i**++) {** 195 anAssignment=weightedSamples . get ( i ) ; 196 aValue=anAssignment . value / normalizer ; 197 aProposition = anAssignment . attribute ; 198 i f ( aProposition . compareTo ( theZero **) !=0)** add ( aProposition , aValue ) ;
199 }
200 r e t u r n Z / ( Z+normalizer ) ; **// r e t u r n th e p e r c e n t a g e o f r e j e c t**
201 }
202 203 **p u b l i c** Assignment <Prop> makeSample **( ) {** 204 Assignment <Prop> assignment = new Assignment <Prop **>() ;** 205 assignment . value **= 1 . ;**
206 assignment . attribute=mappedAttribute . get ( drawTable_sampler **( ) ) .** attribute ;
207 **r e t u r n** assignment ;
208 }
209 210 **p u b l i c b o o l e an** setFuser ( sB left , sB right , 211 RefereeFunctionDefault <Prop> theRefereeFunction ) { 212 ArrayList <sB> bbaTab= new ArrayList <sB **>() ;** 213 bbaTab . add ( left ) ;
214 bbaTab . add ( right ) ;