removing unused C code

Author: jonathan-taylor

selectiveInference/src/Rcpp-debias.cpp

@@ -68,68 +68,3 @@ Rcpp::List solve_QP(Rcpp::NumericMatrix Sigma,
 			    Rcpp::Named("max_active_check") = max_active_check));
 
 }
-
-// [[Rcpp::export]]
-Rcpp::List find_one_row_debiasingM(Rcpp::NumericMatrix Sigma,
-				   int row, // 0-based 
-				   double bound,
-				   int maxiter,
-				   Rcpp::NumericVector theta,
-				   Rcpp::NumericVector gradient,
-				   Rcpp::IntegerVector ever_active,
-				   Rcpp::IntegerVector nactive,
-				   double kkt_tol,
-				   double objective_tol,
-				   int max_active
-				   ) {
-
-  int nrow = Sigma.nrow(); // number of features
-
-  // Active set
-
-  int irow;
-
-  // Extract the diagonal
-  Rcpp::NumericVector Sigma_diag(nrow);
-  double *sigma_diag_p = Sigma_diag.begin();
-
-  for (irow=0; irow<nrow; irow++) {
-    sigma_diag_p[irow] = Sigma(irow, irow);
-  }
-  
-  // Now call our C function
-
-  int iter = find_one_row_((double *) Sigma.begin(),
-			   (double *) Sigma_diag.begin(),
-			   (double *) gradient.begin(),
-			   (int *) ever_active.begin(),
-			   (int *) nactive.begin(),
-			   nrow,
-			   bound,
-			   (double *) theta.begin(),
-			   maxiter,
-			   row,
-			   kkt_tol,
-			   objective_tol,
-			   max_active);
-  
-  // Check whether feasible
-
-  int kkt_check = check_KKT(theta.begin(),
-			    gradient.begin(),
-			    nrow,
-			    row,
-			    bound,
-			    kkt_tol);
-
-  int max_active_check = (*(nactive.begin()) >= max_active);
-
-  return(Rcpp::List::create(Rcpp::Named("soln") = theta,
-			    Rcpp::Named("gradient") = gradient,
-			    Rcpp::Named("iter") = iter,
-			    Rcpp::Named("kkt_check") = kkt_check,
-			    Rcpp::Named("ever_active") = ever_active,
-			    Rcpp::Named("nactive") = nactive,
-			    Rcpp::Named("max_active_check") = max_active_check));
-
-}