You would probably want to use something like the unordered_set
to implement intersect
:
File myintersect.cpp
:
#include <Rcpp.h>
using namespace Rcpp;
// Enable C++11 via this plugin (Rcpp 0.10.3 or later)
// [[Rcpp::plugins(cpp11)]]
// [[Rcpp::export]]
NumericVector myintersect(NumericVector x, NumericVector y) {
std::vector<double> res;
std::unordered_set<double> s(y.begin(), y.end());
for (int i=0; i < x.size(); ++i) {
auto f = s.find(x[i]);
if (f != s.end()) {
res.push_back(x[i]);
s.erase(f);
}
}
return Rcpp::wrap(res);
}
We can load the function and verify it works:
library(Rcpp)
sourceCpp(file="myintersect.cpp")
set.seed(144)
x <- c(-1, -1, sample(seq(1000000), 10000, replace=T))
y <- c(-1, sample(seq(1000000), 10000, replace=T))
all.equal(intersect(x, y), myintersect(x, y))
# [1] TRUE
However, it seems this approach is a good deal less efficient than the itersect
function:
library(microbenchmark)
microbenchmark(intersect(x, y), myintersect(x, y))
# Unit: microseconds
# expr min lq median uq max neval
# intersect(x, y) 424.167 495.861 501.919 523.7835 989.997 100
# myintersect(x, y) 1778.609 1798.111 1808.575 1835.1570 2571.426 100