na.locf and inverse.rle in Rcpp

r, rcpp

Solution

The only thing I'd say is that you are testing for `NA` twice for each value when you only need to do it once. Testing for `NA` is not a free operation. Perhaps something like this:

//[[Rcpp::export]]
NumericVector naLocf(NumericVector x) {
    int n = x.size() ;
    double v = x[0]
    for( int i=1; i<n; i++){
        if( NumericVector::is_na(x[i]) ) {
            x[i] = v ;
        } else {
            v = x[i] ;    
        }
    }

    return x;
}

This still however does unnecessary things, like setting `v` every time when we could only do it for the last time we don't see `NA`. We can try something like this:

//[[Rcpp::export]]
NumericVector naLocf3(NumericVector x) {
    double *p=x.begin(), *end = x.end() ;
    double v = *p ; p++ ;

    while( p < end ){
        while( p<end && !NumericVector::is_na(*p) ) p++ ;
        v = *(p-1) ;
        while( p<end && NumericVector::is_na(*p) ) {
            *p = v ;
            p++ ;
        }
    }

    return x;
}

Now, we can try some benchmarks:

x <- rnorm(1e6)
x[sample(1:1e6, 1000)] <- NA 
require(microbenchmark)
microbenchmark( naLocf1(x), naLocf2(x), naLocf3(x) )
#  Unit: milliseconds
#       expr      min       lq   median       uq      max neval
# naLocf1(x) 6.296135 6.323142 6.339132 6.354798 6.749864   100
# naLocf2(x) 4.097829 4.123418 4.139589 4.151527 4.266292   100
# naLocf3(x) 3.467858 3.486582 3.507802 3.521673 3.569041   100

Problem

I wanted to check if there is any pre-existing trick for `na.locf` (from `zoo` package), `rle` and `inverse.rle` in `RCpp`? I wrote a loop to implement, e.g. I did the implementation of `na.locf(x, na.rm=FALSE, fromLast=FALSE)` as follows: ``` #include <Rcpp.h> using namespace Rcpp; //[[Rcpp::export]] NumericVector naLocf(NumericVector x) { int n=x.size(); for (int i=1;i<n;i++) { if (R_IsNA(x[i]) & !R_IsNA(x[i-1])) { x[i]=x[i-1]; } } return x; } ``` I was just wondering that since these are quite basic functions, someone might have already implemented them in `RCpp` in a better way (may be avoid the loop) OR a faster way?

Original source