R - use primitive functions like max(), sum() in Rcpp - c++

Question

The following codes:
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::export]]
NumericVector FFF(){
NumericVector LB(3);
LB[0]=Language("max",12.3,1.2,13.3,34,10,12.45).eval();
LB[1]=Language("min",12.31,1.24,13.35,340,109,121.45).eval();
LB[2]=Language("sum",12.37,1.21,13.43,34).eval();
return LB;
}
won't pass the compiler, since "Language("max",12.3,1.2,13.3,34,10,12.45).eval())" returns SEXP object, which doesn't fit LB[0]'s type "double". I really want to directly use max(), min() and sum() from the R base instead of writing additional C++ functions. Do you have any good idea?
Thank you!

Answer 1

This is a perfect use case for Rcpp Sugar
http://dirk.eddelbuettel.com/code/rcpp/Rcpp-sugar.pdf
http://adv-r.had.co.nz/Rcpp.html#rcpp-sugar
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::export]]
NumericVector FFF(){
NumericVector LB(3);
LB[0] = max(NumericVector::create(12.3,1.2,13.3,34,10,12.45));
LB[1] = min(NumericVector::create(12.31,1.24,13.35,340,109,121.45));
LB[2] = sum(NumericVector::create(12.37,1.21,13.43,34));
return LB;
}

Answer 2

I like Eigen:
// [[Rcpp::depends(RcppEigen)]]
#include <RcppEigen.h>
using namespace Rcpp;
using Eigen::Map;
using Eigen::VectorXd;
typedef Map<VectorXd> MapVecd;
// [[Rcpp::export]]
NumericVector RcppEigenFun(NumericVector xx) {
const MapVecd x(as<MapVecd>(xx));
NumericVector LB(3);
LB[0] = x.minCoeff();
LB[1] = x.maxCoeff();
LB[2] = x.sum();
return LB;
}
Using it:
RcppEigenFun(3:7)
#[1] 3 7 25
Here is the corresponding function that uses sugar:
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::export]]
NumericVector RcppFun(NumericVector x) {
NumericVector LB(3);
LB[0] = min(x);
LB[1] = max(x);
LB[2] = sum(x);
return LB;
}
Benchmarks:
set.seed(42)
x <- rnorm(1e5)
library(microbenchmark)
microbenchmark(RcppEigenFun(x), RcppFun(x))
#Unit: microseconds
# expr min lq median uq max neval
# RcppEigenFun(x) 101.425 101.807 101.948 102.1785 123.095 100
# RcppFun(x) 1480.187 1480.552 1480.889 1489.0045 1550.173 100