Original motivation behind this is that I have a dynamically sized array of floats that I want to pass to R through Rcpp without either incurring the cost of a zeroing out nor the cost of a deep copy.

Originally I had thought that there might be some way to take heap allocated array, make it aware to R's gc system and then wrap it with other data to create a "Rcpp::NumericVector" but it seems like that that's not possible - or doable with my current knowledge.

However and correct me if I'm wrong it looks like simply constructing a NumericVector with a size N and then using it as an N sized allocation will call R.h's Rf_allocVector and that itself does not either zero out the allocated array - I tested it on a small C program that gets dyn.loaded into R and it looks like garbage values. I also took a peek at the assembly and there doesn't seem to be any zeroing out.

Can anyone confirm this or offer any alternate solution?

CodePudding user response：

Welcome to StackOverflow.

You marked this rcpp but that is a function from the C API of R -- whereas the Rcpp API offers you its constructors which do in fact set the memory tp zero:

> Rcpp::cppFunction("NumericVector goodVec(int n) { return NumericVector(n); }")
> sum(goodVec(1e7))
[1] 0
> 

This creates a dynamically allocated vector using R's memory functions. The vector is indistinguishable from R's own. And it has the memory set to zero as we use R_Calloc, which is documented in Writing R Extension to setting the memory to zero. (We may also use memcpy() explicitly, you can check the sources.)

So in short, you just have yourself confused over what the C API of R, as well as Rcpp offer, and what is easiest to use when. Keep reading documentation, running and writing examples, and studying existing code. It's all out there!