Jeff Brown wrote:> > Hi, > > I'm trying to learn to use .C, which lets one invoke compiled C code from > within R. To do that, one has to first get the C code into R as a shared > object, which (I think) means first compiling it (with COMPILE or SHLIB) > and then loading it (with dyn.load()). >I would suggest taking it a step further and building an R package to hold your compiled code. The pros are: * It keeps the R wrapper scripts and other things you will end up creating packaged together with your code. * It handles compilation automagically during installation. * It handles loading the dylib for you. The only con I can think of is: * It takes ~2 extra minutes of your time to set up. But compared to other languages I have used this is a ridiculously small price to pay for the portability and organization offered by packages. I wrote a post that goes through step-by-step how to do this for the .Call() interface, including example code. You can find it at: http://n4.nabble.com/Writing-own-simulation-function-in-C-td1580190.html#a1580423 In "Writing R Extensions", p. 79, they give the following example of a C program for convolution of two vectors. (The details aren't important; it's just a function that does something to some stuff.) void convolve (double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++) ab[i] = 0.0; for(i = 0; i < *na; i++) for(j = 0; j < *nb; j++) ab[i + j] += a[i] * b[j] } Jeff Brown wrote:> > The document suggests calling it from R like this (again the details > aren't important): > > conv <- function(a, b) > .C("convolve", > as.double(a), > as.integer(length(a)), > as.double(b), > as.integer(length(b)), > ab = double(length(a) + length(b) - 1))$ab > > I wrote a file, "convolve.c", with nothing but the above C code in it. I > can't figure out how to compile it. I don't understand the syntax (no > parentheses?) and I always get the same information-free error message: > >> list.files() > [1] "AER" "convolve.c" "sendmailR" >> R CMD SHLIB "compile.c" > Error: syntax error >> COMPILE "compile.c" > Error: syntax error >> R CMD SHLIB "compile" > Error: syntax error >> COMPILE "compile" > Error: syntax error >> R CMD SHLIB compile.c > Error: syntax error >> COMPILE compile.c > Error: syntax error >> R CMD SHLIB compile > Error: syntax error >> COMPILE compile > Error: syntax error > > I'm using an Intel MacBook Pro running Leopard. At a console, typing "gcc > --version" yields 4.2.1. I know I'm supposed to be using version 4.2; I > thought 4.2.1 would qualify, but please let me know if I'm wrong about > that. > > For guidance I've been relying on "Writing R Extensions", "R Installatino > and Administration", the "R for Mac OS X Developer's Page", and the > built-in help. Please let me know if there are other important resources > I've missed. > > Many thanks, > Jeff >All R CMD commands must be executed at the command line- i.e. in a Windows CMD shell or Unix/Linux bash shell. They are not meant for use inside the R interpreter. Hope this helps! -Charlie ----- Charlie Sharpsteen Undergraduate-- Environmental Resources Engineering Humboldt State University -- View this message in context: http://n4.nabble.com/Getting-started-with-C-tp1837912p1837936.html Sent from the R devel mailing list archive at Nabble.com.
That is tremendously helpful. Thanks Charlie! --- On Mon, 4/12/10, Sharpie [via R] <ml-node+1837936-614100331-179239@n4.nabble.com> wrote: From: Sharpie [via R] <ml-node+1837936-614100331-179239@n4.nabble.com> Subject: Re: Getting started with .C To: "Jeff Brown" <dopethatwantscash@yahoo.com> Date: Monday, April 12, 2010, 10:11 PM Jeff Brown wrote: Hi, I'm trying to learn to use .C, which lets one invoke compiled C code from within R. To do that, one has to first get the C code into R as a shared object, which (I think) means first compiling it (with COMPILE or SHLIB) and then loading it (with dyn.load()). I would suggest taking it a step further and building an R package to hold your compiled code. The pros are: * It keeps the R wrapper scripts and other things you will end up creating packaged together with your code. * It handles compilation automagically during installation. * It handles loading the dylib for you. The only con I can think of is: * It takes ~2 extra minutes of your time to set up. But compared to other languages I have used this is a ridiculously small price to pay for the portability and organization offered by packages. I wrote a post that goes through step-by-step how to do this for the .Call() interface, including example code. You can find it at: http://n4.nabble.com/Writing-own-simulation-function-in-C-td1580190.html#a1580423 In "Writing R Extensions", p. 79, they give the following example of a C program for convolution of two vectors. (The details aren't important; it's just a function that does something to some stuff.) void convolve (double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++) ab[i] = 0.0; for(i = 0; i < *na; i++) for(j = 0; j < *nb; j++) ab[i + j] += a[i] * b[j] } Jeff Brown wrote: The document suggests calling it from R like this (again the details aren't important): conv <- function(a, b) .C("convolve", as.double(a), as.integer(length(a)), as.double(b), as.integer(length(b)), ab = double(length(a) + length(b) - 1))$ab I wrote a file, "convolve.c", with nothing but the above C code in it. I can't figure out how to compile it. I don't understand the syntax (no parentheses?) and I always get the same information-free error message:> list.files()[1] "AER" "convolve.c" "sendmailR"> R CMD SHLIB "compile.c"Error: syntax error> COMPILE "compile.c"Error: syntax error> R CMD SHLIB "compile"Error: syntax error> COMPILE "compile"Error: syntax error> R CMD SHLIB compile.cError: syntax error> COMPILE compile.cError: syntax error> R CMD SHLIB compileError: syntax error> COMPILE compileError: syntax error I'm using an Intel MacBook Pro running Leopard. At a console, typing "gcc --version" yields 4.2.1. I know I'm supposed to be using version 4.2; I thought 4.2.1 would qualify, but please let me know if I'm wrong about that. For guidance I've been relying on "Writing R Extensions", "R Installatino and Administration", the "R for Mac OS X Developer's Page", and the built-in help. Please let me know if there are other important resources I've missed. Many thanks, Jeff All R CMD commands must be executed at the command line- i.e. in a Windows CMD shell or Unix/Linux bash shell. They are not meant for use inside the R interpreter. Hope this helps! -CharlieCharlie Sharpsteen Undergraduate-- Environmental Resources Engineering Humboldt State University View message @ http://n4.nabble.com/Getting-started-with-C-tp1837912p1837936.html To unsubscribe from Getting started with .C, click here. -- View this message in context: http://n4.nabble.com/Getting-started-with-C-tp1837912p1837955.html Sent from the R devel mailing list archive at Nabble.com. [[alternative HTML version deleted]]
On 12 April 2010 at 18:11, Sharpie wrote: | Jeff Brown wrote: | > I'm trying to learn to use .C, which lets one invoke compiled C code from | > within R. To do that, one has to first get the C code into R as a shared | > object, which (I think) means first compiling it (with COMPILE or SHLIB) | > and then loading it (with dyn.load()). | > | | I would suggest taking it a step further and building an R package to hold | your compiled code. The pros are: | | * It keeps the R wrapper scripts and other things you will end up | creating packaged together with your code. | | * It handles compilation automagically during installation. | | * It handles loading the dylib for you. All good reasone, but see below for an even easier solution to get going. | The only con I can think of is: | | * It takes ~2 extra minutes of your time to set up. But compared to | other languages I have used this is a ridiculously small price to pay for | the portability and organization offered by packages. | | I wrote a post that goes through step-by-step how to do this for the .Call() | interface, including example code. You can find it at: | | | http://n4.nabble.com/Writing-own-simulation-function-in-C-td1580190.html#a1580423 | | | | In "Writing R Extensions", p. 79, they give the following example of a C | program for convolution of two vectors. (The details aren't important; it's | just a function that does something to some stuff.) | | void convolve (double *a, int *na, double *b, int *nb, double *ab) { | int i, j, nab = *na + *nb - 1; | for(i = 0; i < nab; i++) | ab[i] = 0.0; | for(i = 0; i < *na; i++) | for(j = 0; j < *nb; j++) | ab[i + j] += a[i] * b[j] | } And all this is even easier if you use the excellent inline package. No Makefiles, no linking, no loading, it all "just works" on all three major platforms: - define the code you want in a variable, here 'code' this does not include the function header - define the function signature - call the 'cfunction' from package inline to compile, link and load the generated function - use it! Here is a live example: R> library(inline) # load inline R> code <- "int i, j, nab = *na + *nb - 1; + for(i = 0; i < nab; i++) + ab[i] = 0.0; + for(i = 0; i < *na; i++) { + for(j = 0; j < *nb; j++) + ab[i + j] += a[i] * b[j]; + }" R> fun <- cfunction(signature(a="numeric", na="numeric", b="numeric", nb="numeric", ab="numeric"), + code, language="C", convention=".C") R> str(fun) # check what the new fun object is Formal class 'CFunc' [package "inline"] with 2 slots ..@ .Data:function (a, na, b, nb, ab) ..@ code : chr "#include <R.h>\n\n\nvoid file46e87ccd ( double * a, double * na, double * b, double * nb, double * ab ) {\nint i, j, nab = *na "| __truncated__ R> fun( 1:10, 10, 4:12, 9, numeric(18))$ab [1] 4 13 28 50 80 119 168 228 300 372 400 413 410 390 352 295 218 120 R> Voila, and we extended R at the command prompt. I'd still recommed .Call over .C, whether you use C++ (which I also recommend :) or C. I have a number of examples for this in the 'Introduction to High-Performance Computing with R' tutorials I have given the last few years, see the slides at http://dirk.eddelbuettel.com/presentations.html as well as the recent UCLA talks on more inline examples with Rcpp (if you want C++). Cheers, Dirk -- Registration is open for the 2nd International conference R / Finance 2010 See http://www.RinFinance.com for details, and see you in Chicago in April!