(This article was first published on

**ECONinfo » Rblogger**, and kindly contributed to R-bloggers)I currently am reading a bit about using Rcpp and its potential for speeding up R. I found one unexpected example in the lecture from Hadley Wickham:

```
require(Rcpp)
signR <- function(x) {
if (x > 0) {
1
} else if (x == 0) {
0
} else {
-1
}
}
cppFunction('int signC(int x) {
if (x > 0) {
return 1;
} else if (x == 0) {
return 0;
} else {
return -1;
}
}')
require(microbenchmark)
microbenchmark(signC(rnorm(1)), signR(rnorm(1)),times = 1e5)
```

## Unit: microseconds ## expr min lq median uq max neval ## signC(rnorm(1)) 2.832 3.186 3.540 3.54 4130 1e+05 ## signR(rnorm(1)) 2.478 3.186 3.186 3.54 2641 1e+05

As expected, the two versions perform nearly identical. Now for the surprise: I changed the scalar version of signC into a vectorized version:

```
library(Rcpp)
cppFunction('IntegerVector signCVec(NumericVector x){
int n = x.size();
IntegerVector out(n);
for(int i = 0; i < n; i++){
if(x[i] > 0 ){
out[i] = 1;
} else if(x[i] == 0){
out[i] = 0;
} else {
out[i] = -1;
}
}
return out;
}
')
signRVec <- function(x) {
ifelse(x > 0,1, ifelse(x == 0,0,-1))
}
```

Now I would have expected the two functions also to be rather similar in execution, but see for yourself:

```
x = rnorm(1e6)
microbenchmark(signCVec(x), signRVec(x),times = 10)
```

## Unit: milliseconds ## expr min lq median uq max neval ## signCVec(x) 8.07 8.103 8.311 8.761 8.952 10 ## signRVec(x) 571.91 581.988 607.664 620.322 743.546 10

Wow: A 60-odd-times reduction using Rcpp.

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