Collect cout or output as vector in recursive function - c++

Question

I have a recursive function that prints a some in nodes in a tree as integer ids. After exporting the function to R, I cannot use the cout output for anything (or so it seems). What would be ideal is if (1) I can return the output as a vector or (2) parse the cout inside R without losing too much speed.
I would insert some code here but my function is particularly generic. Essentially I'm trying to return, say, the Fibonacci sequence as a vector instead of a sum but through a recursive function without using global or static variables.
For example, fib(6) would return inside R as:
[1] 0 1 1 2 3 5
So one could,
y <- fib(6)
y[4] and y[4:5] would return respectively,
[1] 2
[1] 2 3
Thanks in advance for insights and ideas in problem solving. Using a static variable was as far as I got on my own.

Answer 1

I discuss this problem at length with different hashing and memoization implementation in both R and C++ in chapter one of the Rcpp book.

Answer 2

You should read this online book http://adv-r.had.co.nz/, and mostly the memoization part where your question is partly answered http://adv-r.had.co.nz/Function-operators.html:
Just add the function fib3 such as:
library(memoise)
fib2 <- memoise(function(n) {
if (n < 2) return(1)
fib2(n - 2) + fib2(n - 1)
})
fib3 <- memoise(function(n) sapply(1:n, fib2))
#> fib3(6)
#[1] 1 2 3 5 8 13

Answer 3

Just for fun, a slightly more involved approach that uses std::generate_n and a function object (fseq) in lieu of sapply:
#include <Rcpp.h>
struct fseq {
public:
fseq() {
current = 0;
}
int operator()() {
int val = fib(current);
current++;
return val;
}
int fib(int n) {
if (n==0) return 0;
if (n==1) return 1;
return fib(n-2) + fib(n-1);
}
private:
int current;
};
// [[Rcpp::export(".fib")]]
int fib(int n) {
if (n==0) return 0;
if (n==1) return 1;
return fib(n-2) + fib(n-1);
}
// [[Rcpp::export]]
std::vector<int> fib_seq(const int n) {
if (n < 1) throw std::invalid_argument("n must be >= 1");
std::vector<int> seq;
seq.reserve(n);
std::generate_n(std::back_inserter(seq), n, fseq());
return seq;
}
library(microbenchmark)
##
R> fib_seq(6)
[1] 0 1 1 2 3 5
R> all.equal(fib_seq(6),.fib_seq(6))
[1] TRUE
.fib_seq <- function(n) sapply(0:(n-1), .fib)
##
R> microbenchmark(
fib_seq(6),.fib_seq(6),
times=1000L,unit="us")
Unit: microseconds
expr min lq mean median uq max neval
fib_seq(6) 1.561 1.9015 3.287824 2.108 2.3430 1046.021 1000
.fib_seq(6) 27.239 29.0615 35.538355 30.290 32.8065 1108.266 1000
R> microbenchmark(
fib_seq(15),.fib_seq(15),
times=100L,unit="us")
Unit: microseconds
expr min lq mean median uq max neval
fib_seq(15) 6.108 6.5875 7.46431 7.0795 7.7590 20.391 100
.fib_seq(15) 57.243 60.7195 72.97281 63.8120 73.4045 231.707 100
R> microbenchmark(
fib_seq(28),.fib_seq(28),
times=100L,unit="us")
Unit: microseconds
expr min lq mean median uq max neval
fib_seq(28) 2134.861 2143.489 2222.018 2167.364 2219.400 2650.854 100
.fib_seq(28) 3705.492 3721.586 3871.314 3745.956 3852.516 5040.827 100
Note that these functions were parametrized to reflect your statement
For example, fib(6) would return inside R as:
[1] 0 1 1 2 3 5