inline (version 0.2.1)

cfunction: Inline C/C++ function calls from R

Description

The function allows to dynamically define an R-function with inline C or C++ code using the .Call call mechanism of R.

Usage

cfunction(sig=character(), body=character(), includes=character(), cpp=TRUE, verbose=FALSE)
  ## S4 methods for signatures
  #  f='character', sig='list', body='list'
  #  f='character', sig='character', body='character'
  
  setCMethod(f, sig, body, ...)
  ## Further arguments:
  #  setCMethod(f, sig, body, includes="", cpp=TRUE, verbose=FALSE, where=topenv(.GlobalEnv), ...)

Arguments

f

A character value if sig and body are character vectors or a character vector of the same length and the length of sig or body with the name(s) of methods to create.

sig

A match of formal argument names for the function with the character-string names of corresponding classes. In case of setCMethod with signature list -- a list of such character vectors.

body

A character vector of C/C++ code starting after the C-function opening curly bracket and ending before the C-function closing curly bracket, brackets should not be inlcuded. In case of setCMethod with signature list

includes

A character vector of additional includes and preprocessor statements etc that will be put between the R includes and the user function.

cpp

A logical value that specifies if C++ code (and compiler) should be used over C. In this case all functions are additionally listed in the extern "C" clause.

verbose

If TRUE outputs the full compilation output, the source code of the resulting C/C++ program and the definitions of all declared methods. If FALSE, the function is silent, but outputs compiler warning and error message

...

Reserved, passed to .Call.

Value

• cfunction returns an object of class function. setCMethod declares new methods with given names and signatures and returns invisible NULL.

concept

inline function call

Details

To declare multiple functions in the same library one can use setCMethod supplying lists of signatures and implementations. In this case, provide as many method names in f as you define methods. Avoid clashes when selecting names of the methods to declare, i.e. if you provide the same name several times you must ensure that signatures are different but can share the same generic!

The C/C++ code in the body must start after the C-function opening curly bracket and end before the C-function closing curly bracket, brackets should not be inlcuded. The C/C++ function definition and signature will be automatically generated from the R-signature argument. C/C++ variables will carry the same name, therefore please avoid variables with dots. The .Call mechanism is used in this implementation and its result is returned directly as the result of the call of the generated function. As the last line of the generated C/C++ code a return R_NilValue; is added and a warning is generated in case the user has forgotten to provide a return value. To suppress the warning ans still return NULL, add the same line in your code. Special care is needed with types, memory allocation and protection -- exactly the same like if the C/C++ code were not inline: see the Writing R Extension manual for information on .Call. Attached R includes include R.h, Rdefines.h and R_ext\Error.h.

See Also

.Call

Examples

code <- readLines(textConnection("SEXP res;
int nprotect = 0, nx, ny, nz, x, y;
PROTECT(res = Rf_duplicate(a)); nprotect++;
nx = INTEGER(GET_DIM(a))[0];
ny = INTEGER(GET_DIM(a))[1];
nz = INTEGER(GET_DIM(a))[2];
double sigma2 = REAL(s)[0] * REAL(s)[0], d2 ;
double cx = REAL(centre)[0], cy = REAL(centre)[1], *data, *rdata;
for (int im = 0; im < nz; im++) {
  data = &(REAL(a)[im*nx*ny]); rdata = &(REAL(res)[im*nx*ny]);
  for (x = 0; x < nx; x++)
    for (y = 0; y < ny; y++) {
      d2 = (x-cx)*(x-cx) + (y-cy)*(y-cy);
      rdata[x + y*nx] = data[x + y*nx] * exp(-d2/sigma2);
    }
}
UNPROTECT(nprotect);
return res;
"))

x <- array(runif(50*50), c(50,50,1))

funx <- cfunction(signature(a="array", s="numeric", centre="numeric"), code)
res <- funx(a=x, s=10, centre=c(25,15))
image(res[,,1])

setCMethod("funy", signature(a="array", s="numeric", centre="numeric"), code, verbose=TRUE)
res <- funy(x, 10, c(35,35))
x11()
image(res[,,1])