# Using the Rcpp sugar function clamp

January 7, 2013
By

(This article was first published on Rcpp Gallery, and kindly contributed to R-bloggers)

Since the 0.10.* release series, Rcpp contains a new sugar function clamp which can be used to limit vectors to both a minimum and maximim value. This recent StackOverflow question permitted clamp to shine. We retake some of the answers, including the clamp entry by Romain.

We first define the three R versions.

pminpmaxClamp <- function(x, a, b) {
pmax(a, pmin(x, b) )
}

ifelseClamp <- function(x, a, b) {
ifelse(x <= a,  a, ifelse(x >= b, b, x))
}

operationsClamp <- function(x, a, b) {
a + (x-a > 0)*(x-a) - (x-b > 0)*(x-b)
}

We then define some data, and ensure that these versions all producing identical results.

set.seed(42)
x <- rnorm(100000)

a <- -1.0
b <- 1.0
stopifnot(all.equal(pminpmaxClamp(x,a,b), ifelseClamp(x,a,b), operationsClamp(x,a,b)))

Next is the C++ solution: a one-liner thanks to the existing sugar function.

#include <Rcpp.h>

using namespace Rcpp;

// [[Rcpp::export]]
NumericVector rcppClamp(NumericVector x, double mi, double ma) {
return clamp(mi, x, ma);
}

We can then check and benchmark the new C++ version.

stopifnot(all.equal(pminpmaxClamp(x,a,b), rcppClamp(x,a,b)))

library(rbenchmark)
benchmark(pminpmaxClamp(x, a, b),
ifelseClamp(x, a, b),
operationsClamp(x, a, b),
rcppClamp(x, a, b),
order="relative")[,1:4]
test replications elapsed relative
4       rcppClamp(x, a, b)          100   0.119    1.000
3 operationsClamp(x, a, b)          100   0.505    4.244
1   pminpmaxClamp(x, a, b)          100   0.530    4.454
2     ifelseClamp(x, a, b)          100   5.268   44.269

We see a decent gain of the Rcpp version even relative to these vectorised R solutions. Among these, the simplest (based on ifelse) is by far the slowest. The parallel min/max version is about as faster as the clever-but-less-readable expression-based solution.

Real “production” solutions will of course need some more testing of inputs etc. However, as an illustration of clamp this example has hopefully been compelling.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

## Recent popular posts

Contact us if you wish to help support R-bloggers, and place your banner here.

# Never miss an update! Subscribe to R-bloggers to receive e-mails with the latest R posts.(You will not see this message again.)

Click here to close (This popup will not appear again)