Rcpp pass by reference vs. by value

Question

I made a first stab at an Rcpp function via inline and it solved my speed problem (thanks Dirk!): Replace negative values by zero

The initial version looked like this:

library(inline)
cpp_if_src <- '
  Rcpp::NumericVector xa(a);
  int n_xa = xa.size();
  for(int i=0; i < n_xa; i++) {
    if(xa[i]<0) xa[i] = 0;
  }
  return xa;
'
cpp_if <- cxxfunction(signature(a="numeric"), cpp_if_src, plugin="Rcpp")

But when called cpp_if(p), it overwrote p with the output, which was not as intended. So I assumed it was passing by reference.

So I fixed it with the following version:

library(inline)
cpp_if_src <- '
  Rcpp::NumericVector xa(a);
  int n_xa = xa.size();
  Rcpp::NumericVector xr(a);
  for(int i=0; i < n_xa; i++) {
    if(xr[i]<0) xr[i] = 0;
  }
  return xr;
'
cpp_if <- cxxfunction(signature(a="numeric"), cpp_if_src, plugin="Rcpp")

Which seemed to work. But now the original version doesn't overwrite its input anymore when I re-load it into R (i.e. the same exact code now doesn't overwrite its input):

> cpp_if_src <- '
+   Rcpp::NumericVector xa(a);
+   int n_xa = xa.size();
+   for(int i=0; i < n_xa; i++) {
+     if(xa[i]<0) xa[i] = 0;
+   }
+   return xa;
+ '
> cpp_if <- cxxfunction(signature(a="numeric"), cpp_if_src, plugin="Rcpp")
> 
> p
 [1] -5 -4 -3 -2 -1  0  1  2  3  4  5
> cpp_if(p)
 [1] 0 0 0 0 0 0 1 2 3 4 5
> p
 [1] -5 -4 -3 -2 -1  0  1  2  3  4  5

I'm not the only one who has tried to replicate this behavior and found inconsistent results:

https://chat.stackoverflow.com/transcript/message/4357344#4357344

What's going on here?

Answer 1

They key is 'proxy model' -- your xa really is the same memory location as your original object so you end up changing your original.

If you don't want that, you should do one thing: (deep) copy using the clone() method, or maybe explicit creation of a new object into which the altered object gets written. Method two does not do that, you simply use two differently named variables which are both "pointers" (in the proxy model sense) to the original variable.

An additional complication, though, is in implicit cast and copy when you pass an int vector (from R) to a NumericVector type: that creates a copy, and then the original no longer gets altered.

Here is a more explicit example, similar to one I use in the tutorials or workshops:

library(inline)
f1 <- cxxfunction(signature(a="numeric"), plugin="Rcpp", body='
  Rcpp::NumericVector xa(a);
  int n = xa.size();
  for(int i=0; i < n; i++) {
    if(xa[i]<0) xa[i] = 0;
  }
  return xa;
')

f2 <- cxxfunction(signature(a="numeric"), plugin="Rcpp", body='
  Rcpp::NumericVector xa(a);
  int n = xa.size();
  Rcpp::NumericVector xr(a);            // still points to a
  for(int i=0; i < n; i++) {
    if(xr[i]<0) xr[i] = 0;
  }
  return xr;
')

p <- seq(-2,2)
print(class(p))
print(cbind(f1(p), p))
print(cbind(f2(p), p))
p <- as.numeric(seq(-2,2))
print(class(p))
print(cbind(f1(p), p))
print(cbind(f2(p), p))

and this is what I see:

edd@max:~/svn/rcpp/pkg$ r /tmp/ari.r
Loading required package: methods
[1] "integer"
        p
[1,] 0 -2
[2,] 0 -1
[3,] 0  0
[4,] 1  1
[5,] 2  2
        p
[1,] 0 -2
[2,] 0 -1
[3,] 0  0
[4,] 1  1
[5,] 2  2
[1] "numeric"
       p
[1,] 0 0
[2,] 0 0
[3,] 0 0
[4,] 1 1
[5,] 2 2
       p
[1,] 0 0
[2,] 0 0
[3,] 0 0
[4,] 1 1
[5,] 2 2
edd@max:~/svn/rcpp/pkg$

So it really matters whether you pass int-to-float or float-to-float.