RcppInt64: Bindings for Passing integer64 To And From C++
Motivation
While R has no native support for 64-bit integer values, the
bit64
package by Jens Oehlschlägel is widely used to fill this gap by
(very carefully) passing the bitmaps of int64_t values
around in double. This works on the R side by virtue of a
S3 class integer64 with proper dispatching, and on the
C/C++ side where the values can be past by memcpy. What one
cannot do is simply copying or casting: the tradeoff made in
representing a double with as large a range is that the
‘delta’ between values is not constant acros the range and naive casting
between both representation will be lossy and distort
values.
This package contains helper functions that were previously appearing
in helper header files in different packages, and reorganizes them along
with a proper unit tests. The key header file provided here can be
included directly. Function to assert integer64 source,
convert to and from in both scalar and vector cases as well as a pair of
as<>() and wrap() converters are
provided.
Example
The example for the included demonstration function show how a vector
of integer64 values (here spanning the power of 10 ranging
from 0 to 18) can be received in C++, altered (where we just add one)
and returned, all while maintaining integer64 aka
int64_t type.
> example(Int64toInt64)
I64I64> # generate all powers of 10 fro 0 .. 18
I64I64> v <- bit64::as.integer64(10^seq(0,18))
I64I64> # pass them to function which will add one to each, print and return
I64I64> Int64toInt64(v)
2
11
101
1001
10001
100001
1000001
10000001
100000001
1000000001
10000000001
100000000001
1000000000001
10000000000001
100000000000001
1000000000000001
10000000000000001
100000000000000001
1000000000000000001
integer64
[1] 2 11 101
[4] 1001 10001 100001
[7] 1000001 10000001 100000001
[10] 1000000001 10000000001 100000000001
[13] 1000000000001 10000000000001 100000000000001
[16] 1000000000000001 10000000000000001 100000000000000001
[19] 1000000000000000001
>Contributing
Any problems, bug reports, or features requests for the package can be submitted and handled most conveniently as Github issues in the repository.
Before submitting pull requests, it is frequently preferable to first discuss need and scope in such an issue ticket. See the file Contributing.md (in the Rcpp repo) for a brief discussion.
Author
Dirk Eddelbuettel
License
GPL (>= 2)