# Comparing ifelse with C++ for loop with ifs

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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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