On 01/14/2010 03:50 PM, Dominick Samperi wrote:
The Rcpp library in RcppTemplate (the package that Rcpp forked from)
simplifies the process
of calling functions from C++. The design goal was to enable users to
focus on
scientific problem solving rather than interface problems and low-level
R internals (by
hiding these details and documenting everything).
Hello Dominick,
In the Rcpp package, you'd call the rnorm function like this :
/* grab the environment called "package:stats" */
Environment stats("package:stats") ;
/* or like this if you want the namespace */
/* Environment stats = Environment::namespace_env("stats") ;*/
/* grab function called 'rnorm' from this environment */
Function rnorm = stats.get("rnorm" ) ;
/* call the function, about the same way you'd do in R
*
* > rnorm( 10L, sd = 100 )
*/
return rnorm( 10, Named( "sd", 100.0 ) ) ;
All involved SEXP are encapsulated in suitable C++ objects, such as
Environment, Function, etc ... the user does not need to know about
SEXP, does not need to care about the PROTECT/UNPROTECT dance, etc ...
Please let me know which of these three lines of C++ code you consider
to be low level R internals.
It might be interesting that you post how you would invoke the same
using RcppTemplate.
The current Rcpp package is a mashup of the packages RcppTemplate (old
version),
inline, and RInside
It is not anything even kind of close to that.
There was code from the inline package at some point, but it is now back
into inline, which has been improved to support easy inlining of code
making use of Rcpp.
There is nothing of RInside in Rcpp, it goes the other way, RInside
depends on Rcpp and uses its features to ease embedding R into an
existing C++ application
The Rcpp package is under a lot of changes. See :
- http://dirk.eddelbuettel.com/blog/2010/01/12/#rcpp_0.7.2
- http://dirk.eddelbuettel.com/blog/2010/01/02/#rcpp_0.7.1
-
http://romainfrancois.blog.free.fr/index.php?post/2010/01/13/Rcpp-0.7.2-is-out
-
http://romainfrancois.blog.free.fr/index.php?post/2010/01/08/External-pointers-with-Rcpp
-
http://romainfrancois.blog.free.fr/index.php?post/2009/12/29/new-things-in-Rcpp
that involves a fair amount of low-level R hacking,
and this is
probably consistent with the preferences of most readers of this list.
Can you be more specific ?
The whole purpose of the package is to hide the R API. The user does not
need to know the R API to use the classes of Rcpp. We however indeed use
and abuse the R API a lot internally.
Romain
If I am mistaken and there are any users of RcppTemplate please let me
know, as I
am thinking about reoganizing that package to minimize confusion with
the fork.
Thanks,
Dominick
On Thu, Jan 14, 2010 at 7:16 AM, Romain Francois
<romain.franc...@dbmail.com <mailto:romain.franc...@dbmail.com>> wrote:
On 01/14/2010 12:42 PM, Laurent Gautier wrote:
Hi,
In Rcpp, we now have a "Function" class to encapsulate functions
(they cover all three kinds, but this may change).
Just a note on that: there is probably no hurry to do so.
rpy2 is also having CLOSXP, BUILTINSXP, and SPECIALSXP
represented as
one function-like class and seems to be behave reasonably while
a lot of
other things seem more urgent to sort out.
To call the function, what we do is generate a call with the
function
as the first node and then evaluate the call.
SEXP stats = PROTECT( R_FindNamespace( mkString( "stats") )
); SEXP
rnorm = PROTECT( findVarInFrame( stats, install( "rnorm") )
) ; SEXP
call = PROTECT( LCONS( rnorm, CONS( ScalarInteger(10),
CONS(ScalarReal(0), R_NilValue ) ) ) ); SEXP res = PROTECT(
eval(
call , R_GlobalEnv ) ); UNPROTECT(4) ; return res ;
It works, but I was wondering if there was another way. I've
seen
applyClosure, but I'm not sure I should attempt to use it or
if using
a call like above is good enough.
Using R_tryEval() will let you evaluate an expression in a given
environment, as well as capture an eventual error occurring
during its
evaluation (and translate it as an exception).
Sure. I did not want to over-complicate the question.
I'm currently reviewing tryEval and its underlying R_TopLevelExec
which does not give me enough : when the error occurs, it'd be
useful that the function returns the condition object instead of NULL.
Romain
PS: using Rcpp's C++ classes you would express the code
above as :
Environment stats("package:stats") ; Function rnorm = stats.get(
"rnorm" ) return rnorm( 10, 0.0 ) ;
Feel free to snoop in rpy2's rpy/rinterface/rinterface.c and
look for
"do_try_eval". The behavior looks very similar, the above snippet in
rpy2 would write like:
from rpy2.robjects.packages import importr
stats = importr('stats')
stats.rnorm(10, 0.0)
nice
--
Romain Francois
Professional R Enthusiast
+33(0) 6 28 91 30 30
http://romainfrancois.blog.free.fr
|- http://tr.im/KfKn : Rcpp 0.7.2
|- http://tr.im/JOlc : External pointers with Rcpp
`- http://tr.im/JFqa : R Journal, Volume 1/2, December 2009
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