apply-benchmark.cpp

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
NumericVector rowApply0(NumericMatrix& x, const Function& FUN)
{
  int n = x.nrow();
  NumericVector result = no_init(n);
  
  for (int r = 0; r < n; r++) {
    result[r] = as<double>(FUN(x(r, _) ) );
  }
  return result;
}

// [[Rcpp::export]]
NumericVector rowApply1(NumericMatrix& x, const Function& FUN)
{
  int n = x.nrow();
  NumericVector result = no_init(n);
  
  for (int r = 0; r < n; r++) {
    Language call(FUN, x(r, _)) ;
    result[r] = as<double>(call.fast_eval() );
  }
  return result;
}

// [[Rcpp::export]]
NumericVector rowApply2(NumericMatrix& x, const Function& FUN)
{
  int n = x.nrow();
  NumericVector result = no_init(n);
  
  Language call(FUN, R_NilValue);
  Language::Proxy proxy(call, 1);
  for (int r = 0; r < n; r++) {
    proxy = x(r, _) ;
    result[r] = as<double>(call.fast_eval() );
  }
  return result;
}

/*** R

library(microbenchmark)
options(digits = 3)

M <- matrix(rnorm(15L), nrow=3L);
identical(rowMeans(M), apply(M, 1L, mean));
identical(rowMeans(M), rowApply0(M, mean));
identical(rowMeans(M), rowApply1(M, mean));
identical(rowMeans(M), rowApply2(M, mean));

microbenchmark(rowMeans(M),
  apply(M, 1L, mean),
  rowApply0(M, mean),
  rowApply1(M, mean),
  rowApply2(M, mean))

M <- matrix(rnorm(1500L), nrow=30L);
microbenchmark(rowMeans(M),
  apply(M, 1L, mean),
  rowApply0(M, mean),
  rowApply1(M, mean),
  rowApply2(M, mean))

*/