I have a cppFunction
with a vector ints
as input, eg:
library(Rcpp)
cppFunction('double test2(NumericVector ints) {
return 42;
}')
The output is correct if passing a vector of length at least 1:
> test2(1)
[1] 42
> test2(1:10)
[1] 42
For input of length 0 however I get:
> test2(c())
Error: not compatible with requested type
Is there any way to pass a vector of length 0 or larger to my function? Ie my expected output is:
> test2_expectedoutput(c())
[1] 42
I know I could control for this in R by checking in R first and calling a different version of the function but would like to avoid this. I expect there is some easy solution out there since within cpp I could also have a NumericVector
of length 0 if I understand correctly what NumericVector zero;
does. The only related question I could find was this on how to return a NULL object from within a Rcpp function to R .
A few months ago we added the ability to pass as Nullable<T>
which may be what you want here.
Here is a simple example:
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::export]]
bool checkNull(Nullable<NumericVector> x) {
if (x.isNotNull()) {
// do something
NumericVector xx(x);
Rcpp::Rcout << "Sum is " << sum(xx) << std::endl;
return true;
} else {
// do nothing
Rcpp::Rcout << "Nothing to see" << std::endl;
return false;
}
}
/*** R
checkNull(1:3)
checkNull(NULL)
*/
and its output:
R> sourceCpp("/tmp/null.cpp")
R> checkNull(1:3)
Sum is 6
[1] TRUE
R> checkNull(NULL)
Nothing to see
[1] FALSE
R>
By being templated we respect the intended type but clearly differentiate between being there, and not.
The c()
calls produces NULL
which is not a numeric
vector. This generates the error when test2
is called. You can build a numeric vector of length 0 through numeric
:
#check what `c()` does
str(c())
# NULL
# now we try numeric(0)
test2(numeric(0))
#[1] 42
As a suggestion, I think that C
, Fortran
or C++
functions should rarely be called directly; much better to write a wrapper that does some preliminary operations, like type conversions and similar. Something like the following:
test2Wrapp<-function(x) test2(as.numeric(x))
test2Wrapp(c())
#[1] 42
#This has the benefit to not calling the internal routines in cases where conversion isn't possible
test2Wrapp(iris)
#Error: (list) object cannot be coerced to type 'double'
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