Ross Bennett — written Jan 31, 2013 — source
Consider the problem to sort all elements of the given vector in ascending
order. We can simply use the function std::sort
from the C++ STL.
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::export]]
NumericVector stl_sort(NumericVector x) {
NumericVector y = clone(x);
std::sort(y.begin(), y.end());
return y;
}
library(rbenchmark)
set.seed(123)
z <- rnorm(100000)
x <- rnorm(100)
# check that stl_sort is the same as sort
stopifnot(all.equal(stl_sort(x), sort(x)))
# benchmark stl_sort and sort
benchmark(stl_sort(z), sort(z), order="relative")[,1:4]
test replications elapsed relative 1 stl_sort(z) 100 0.913 1.000 2 sort(z) 100 1.635 1.791
Consider the problem of sorting the first n
elements of a given vector.
The function std::partial_sort
from the C++ STL does just this.
// [[Rcpp::export]]
NumericVector stl_partial_sort(NumericVector x, int n) {
NumericVector y = clone(x);
std::partial_sort(y.begin(), y.begin()+n, y.end());
return y;
}
An alternate implementation of a partial sort algorithm is to use
std::nth_element
to partition the given vector at the nth sorted
element and then use std::sort
, both from the STL, to sort the vector
from the beginning to the nth element.
For an equivalent implementation in R, we can use the sort
function by
specifying a vector of 1:n
for the partial argument (i.e. partial=1:n
).
// [[Rcpp::export]]
NumericVector nth_partial_sort(NumericVector x, int nth) {
NumericVector y = clone(x);
std::nth_element(y.begin(), y.begin()+nth, y.end());
std::sort(y.begin(), y.begin()+nth);
return y;
}
n <- 25000
# check that stl_partial_sort is equal to nth_partial_sort
stopifnot(all.equal(stl_partial_sort(x, 50)[1:50],
nth_partial_sort(x, 50)[1:50]))
# benchmark stl_partial_sort, nth_element_sort, and sort
benchmark(stl_partial_sort(z, n),
nth_partial_sort(z, n),
sort(z, partial=1:n),
order="relative")[,1:4]
test replications elapsed relative 2 nth_partial_sort(z, n) 100 0.335 1.000 1 stl_partial_sort(z, n) 100 0.853 2.546 3 sort(z, partial = 1:n) 100 1.133 3.382
An interesting result to note is the gain in speed of
nth_partial_sort
over stl_partial_sort
. In this case, for the given
data, it is faster to use the combination ofstd::nth_element
and
std::sort
rather than std::partial_sort
to sort the first n
elements
of a vector.
// [[Rcpp::export]]
NumericVector stl_nth_element(NumericVector x, int n) {
NumericVector y = clone(x);
std::nth_element(y.begin(), y.begin()+n-1, y.end());
return y;
}
Finally, consider a problem where you only need a single element of a
sorted vector. The function std::nth_element
from the C++ STL does just
this. An example of this type of problem is computing the median of a given
vector.
For an equivalent implementation in R, we can use the sort
function by
specifying a scalar value for the argument partial (i.e. partial=n
).
# check that the nth sorted elements of the vectors are equal
stopifnot(all.equal(stl_nth_element(x, 43)[43], sort(x, partial=43)[43]))
# benchmark nth_element and sort
benchmark(stl_nth_element(z, n),
sort(z, partial=n),
order="relative")[,1:4]
test replications elapsed relative 1 stl_nth_element(z, n) 100 0.160 1.000 2 sort(z, partial = n) 100 0.466 2.913
While these are not huge speed improvements over the base R sort function, this post demonstrates how to easily access sorting functions in the C++ STL and is a good exercise to better understand the differences and performance of the sorting algorithms available in C++ and R.
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