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jonathan-taylorjonathan-taylor
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Merge pull request #29 from jonathan-taylor/master
removing unused C code - the duplicate version of the C code has been removed - Rcpp exports are now in repo: if we change the wrapper cpp we will need to recommit these
2 parents bbf7e19 + 5e671a4 commit a0034d7

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6 files changed

+73
-428
lines changed

6 files changed

+73
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lines changed

‎selectiveInference/R/RcppExports.R

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# This file was generated by Rcpp::compileAttributes
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# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
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solve_QP <- function(Sigma, bound, maxiter, theta, linear_func, gradient, ever_active, nactive, kkt_tol, objective_tol, max_active) {
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.Call('selectiveInference_solve_QP', PACKAGE = 'selectiveInference', Sigma, bound, maxiter, theta, linear_func, gradient, ever_active, nactive, kkt_tol, objective_tol, max_active)
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}
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update1_ <- function(Q2, w, m, k) {
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.Call('selectiveInference_update1_', PACKAGE = 'selectiveInference', Q2, w, m, k)
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}
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downdate1_ <- function(Q1, R, j0, m, n) {
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.Call('selectiveInference_downdate1_', PACKAGE = 'selectiveInference', Q1, R, j0, m, n)
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}
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‎selectiveInference/src/Makevars

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@@ -2,7 +2,7 @@ PKG_CFLAGS= -I.
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PKG_CPPFLAGS= -I.
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PKG_LIBS=-L.
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$(SHLIB): Rcpp Rcpp-matrixcomps.o Rcpp-debias.o RcppExports.o debias.o
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$(SHLIB): Rcpp Rcpp-matrixcomps.o Rcpp-debias.o RcppExports.o quadratic_program.o
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clean:
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rm -f *o

‎selectiveInference/src/Rcpp-debias.cpp

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

‎selectiveInference/src/RcppExports.cpp

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// This file was generated by Rcpp::compileAttributes
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// Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
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#include <Rcpp.h>
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using namespace Rcpp;
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// solve_QP
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Rcpp::List solve_QP(Rcpp::NumericMatrix Sigma, double bound, int maxiter, Rcpp::NumericVector theta, Rcpp::NumericVector linear_func, Rcpp::NumericVector gradient, Rcpp::IntegerVector ever_active, Rcpp::IntegerVector nactive, double kkt_tol, double objective_tol, int max_active);
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RcppExport SEXP selectiveInference_solve_QP(SEXP SigmaSEXP, SEXP boundSEXP, SEXP maxiterSEXP, SEXP thetaSEXP, SEXP linear_funcSEXP, SEXP gradientSEXP, SEXP ever_activeSEXP, SEXP nactiveSEXP, SEXP kkt_tolSEXP, SEXP objective_tolSEXP, SEXP max_activeSEXP) {
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BEGIN_RCPP
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Rcpp::RObject __result;
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Rcpp::RNGScope __rngScope;
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Rcpp::traits::input_parameter< Rcpp::NumericMatrix >::type Sigma(SigmaSEXP);
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Rcpp::traits::input_parameter< double >::type bound(boundSEXP);
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Rcpp::traits::input_parameter< int >::type maxiter(maxiterSEXP);
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Rcpp::traits::input_parameter< Rcpp::NumericVector >::type theta(thetaSEXP);
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Rcpp::traits::input_parameter< Rcpp::NumericVector >::type linear_func(linear_funcSEXP);
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Rcpp::traits::input_parameter< Rcpp::NumericVector >::type gradient(gradientSEXP);
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Rcpp::traits::input_parameter< Rcpp::IntegerVector >::type ever_active(ever_activeSEXP);
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Rcpp::traits::input_parameter< Rcpp::IntegerVector >::type nactive(nactiveSEXP);
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Rcpp::traits::input_parameter< double >::type kkt_tol(kkt_tolSEXP);
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Rcpp::traits::input_parameter< double >::type objective_tol(objective_tolSEXP);
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Rcpp::traits::input_parameter< int >::type max_active(max_activeSEXP);
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__result = Rcpp::wrap(solve_QP(Sigma, bound, maxiter, theta, linear_func, gradient, ever_active, nactive, kkt_tol, objective_tol, max_active));
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return __result;
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END_RCPP
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}
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// update1_
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Rcpp::List update1_(Rcpp::NumericMatrix Q2, Rcpp::NumericVector w, int m, int k);
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RcppExport SEXP selectiveInference_update1_(SEXP Q2SEXP, SEXP wSEXP, SEXP mSEXP, SEXP kSEXP) {
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BEGIN_RCPP
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Rcpp::RObject __result;
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Rcpp::RNGScope __rngScope;
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Rcpp::traits::input_parameter< Rcpp::NumericMatrix >::type Q2(Q2SEXP);
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Rcpp::traits::input_parameter< Rcpp::NumericVector >::type w(wSEXP);
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Rcpp::traits::input_parameter< int >::type m(mSEXP);
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Rcpp::traits::input_parameter< int >::type k(kSEXP);
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__result = Rcpp::wrap(update1_(Q2, w, m, k));
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return __result;
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END_RCPP
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}
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// downdate1_
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Rcpp::List downdate1_(Rcpp::NumericMatrix Q1, Rcpp::NumericMatrix R, int j0, int m, int n);
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RcppExport SEXP selectiveInference_downdate1_(SEXP Q1SEXP, SEXP RSEXP, SEXP j0SEXP, SEXP mSEXP, SEXP nSEXP) {
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BEGIN_RCPP
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Rcpp::RObject __result;
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Rcpp::RNGScope __rngScope;
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Rcpp::traits::input_parameter< Rcpp::NumericMatrix >::type Q1(Q1SEXP);
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Rcpp::traits::input_parameter< Rcpp::NumericMatrix >::type R(RSEXP);
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Rcpp::traits::input_parameter< int >::type j0(j0SEXP);
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Rcpp::traits::input_parameter< int >::type m(mSEXP);
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Rcpp::traits::input_parameter< int >::type n(nSEXP);
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__result = Rcpp::wrap(downdate1_(Q1, R, j0, m, n));
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return __result;
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END_RCPP
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}

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