35 SWIG and R

R is a GPL'ed open source statistical and plotting environment. Information about R can be found at www.r-project.org. The R bindings are under active development. They have been used to compile and run an R interface to QuantLib running on Mandriva Linux with gcc. The R bindings also work on Microsoft Windows using Visual C++.

35.1 Bugs

Currently the following features are not implemented or broken:

35.2 Using R and SWIG

To use R and SWIG in C mode, execute the following commands where example.c is the name of the file with the functions in them 

swig -r example.i
R CMD SHLIB example_wrap.c example.c

The corresponding options for C++ mode are 

swig -c++ -r -o example_wrap.cpp example.i
R CMD SHLIB example_wrap.cpp example.cpp

Note that R is sensitive to the names of the files. The name of the wrapper file must be the name of the library unless you use the -o option to R when building the library, for example: 

swig -c++ -r -o example_wrap.cpp example.i
R CMD SHLIB -o example.so example_wrap.cpp example.cpp

R is also sensitive to the name of the file extension in C and C++ mode. In C++ mode, the file extension must be .cpp rather than .cxx for the R compile command to recognize it. If your C++ code is in a file using something other than a .cpp extension, then it may still work using PKG_LIBS: 

swig -c++ -r -o example_wrap.cpp example.i
PKG_LIBS="example.cxx" R CMD SHLIB -o example example_wrap.cpp

The commands produces two files. A dynamic shared object file called example.so, or example.dll, and an R wrapper file called example.R. To load these files, start up R and type in the following commands 

dyn.load(paste("example", .Platform$dynlib.ext, sep=""))
source("example.R")
cacheMetaData(1)
The cacheMetaData(1) will cause R to refresh its object tables. Without it, inheritance of wrapped objects may fail.

These two files can be loaded in any order

35.3 Precompiling large R files

In cases where the R file is large, one make save a lot of loading time by precompiling the R wrapper. This can be done by creating the file makeRData.R which contains the following 
source('BigFile.R')
save(list=ls(all=TRUE),file="BigFile.RData", compress=TRUE)
q(save="no")
This will generate a compiled R file called BigFile.RData that will save a large amount of loading time.

35.4 General policy

The general policy of the module is to treat the C/C++ as a basic wrapping over the underlying functions and rely on the R type system to provide R syntax.

35.5 Language conventions

getitem and setitem use C++ conventions (i.e. zero based indices). [<- and [ are overloaded to allow for R syntax (one based indices and slices)

35.6 C++ classes

C++ objects are implemented as external pointer objects with the class being the mangled name of the class. The C++ classes are encapsulated as an SEXP with an external pointer type. The class is the mangled name of the class. The nice thing about R is that is allows you to keep track of the pointer object which removes the necessity for a lot of the proxy class baggage you see in other languages.

35.7 Enumerations

enumerations are characters which are then converted back and forth to ints before calling the C routines. All of the enumeration code is done in R.