1325     CvSVMDecisionFunc* df = 0;  in do_train()  local
1333         CV_CALL( decision_func = df =  in do_train()
1334             (CvSVMDecisionFunc*)cvAlloc( sizeof(df[0]) ));  in do_train()
1336         df->rho = 0;  in do_train()
1338             responses->data.i, 0, 0, temp_storage, alpha, df->rho ))  in do_train()
1344         sv_total = df->sv_count = sv_count;  in do_train()
1345         CV_CALL( df->alpha = (double*)cvMemStorageAlloc( storage, sv_count*sizeof(df->alpha[0])) );  in do_train()
1354                 df->alpha[k++] = alpha[i];  in do_train()
1382         CV_CALL( decision_func = df = (CvSVMDecisionFunc*)cvAlloc(  in do_train()
1383             (class_count*(class_count-1)/2)*sizeof(df[0])));  in do_train()
1421             for( j = i+1; j < class_count; j++, df++ )  in do_train()
1447                              Cp, Cn, temp_storage, alpha, df->rho ))  in do_train()
1453                 df->sv_count = sv_count;  in do_train()
1455                 CV_CALL( df->alpha = (double*)cvMemStorageAlloc( temp_storage,  in do_train()
1456                                                 sv_count*sizeof(df->alpha[0])));  in do_train()
1457                 CV_CALL( df->sv_index = (int*)cvMemStorageAlloc( temp_storage,  in do_train()
1458                                                 sv_count*sizeof(df->sv_index[0])));  in do_train()
1465                         df->sv_index[k1] = si + k;  in do_train()
1466                         df->alpha[k1++] = alpha[k];  in do_train()
1475                         df->sv_index[k1] = sj + k;  in do_train()
1476                         df->alpha[k1++] = alpha[ci + k];  in do_train()
1502         df = (CvSVMDecisionFunc*)decision_func;  in do_train()
1507             for( j = i+1; j < class_count; j++, df++ )  in do_train()
1509                 for( k = 0; k < df->sv_count; k++ )  in do_train()
1511                     df->sv_index[k] = sv_tab[df->sv_index[k]]-1;  in do_train()
1512                     assert( (unsigned)df->sv_index[k] < (unsigned)sv_total );  in do_train()
1915         CvSVMDecisionFunc* df = (CvSVMDecisionFunc*)decision_func;  in predict()  local
1916         int i, sv_count = df->sv_count;  in predict()
1917         double sum = -df->rho;  in predict()
1921             sum += buffer[i]*df->alpha[i];  in predict()
1928         CvSVMDecisionFunc* df = (CvSVMDecisionFunc*)decision_func;  in predict()  local
1937             for( j = i+1; j < class_count; j++, df++ )  in predict()
1939                 double sum = -df->rho;  in predict()
1940                 int sv_count = df->sv_count;  in predict()
1942                     sum += df->alpha[k]*buffer[df->sv_index[k]];  in predict()
2046     const CvSVMDecisionFunc* df = decision_func;  in write()  local
2086     df = decision_func;  in write()
2091         int sv_count = df[i].sv_count;  in write()
2094         cvWriteReal( fs, "rho", df[i].rho );  in write()
2096         cvWriteRawData( fs, df[i].alpha, df[i].sv_count, "d" );  in write()
2101             cvWriteRawData( fs, df[i].sv_index, df[i].sv_count, "i" );  in write()
2207     CvSVMDecisionFunc* df;  in read()  local
2272     CV_CALL( df = decision_func = (CvSVMDecisionFunc*)cvAlloc( df_count*sizeof(df[0]) ));  in read()
2283         df[i].sv_count = sv_count;  in read()
2285         df[i].rho = cvReadRealByName( fs, df_elem, "rho", not_found_dbl );  in read()
2286         if( fabs(df[i].rho - not_found_dbl) < DBL_EPSILON )  in read()
2292         CV_CALL( df[i].alpha = (double*)cvMemStorageAlloc( storage,  in read()
2293                                         sv_count*sizeof(df[i].alpha[0])));  in read()
2296         CV_CALL( cvReadRawData( fs, alpha_node, df[i].alpha, "d" ));  in read()
2303             CV_CALL( df[i].sv_index = (int*)cvMemStorageAlloc( storage,  in read()
2304                                             sv_count*sizeof(df[i].sv_index[0])));  in read()
2307             CV_CALL( cvReadRawData( fs, index_node, df[i].sv_index, "i" ));  in read()
2310             df[i].sv_index = 0;  in read()