![]() We’ll supply a value of 5 for “n” and we’ll pass a single integer as a value for the “answer” variable though that will be overwritten once the subroutine computes the “answer”. Keep in mind that the subroutine “facto” has two arguments both of which are integers. ![]() To do that we rely upon the “.Fortran” function. ![]() What’s going on ? Well all we did was simply load the shared object. It’s purpose is to load/unload shared objects which are also known as DLLs, (dynamically loadable libraries). We’ll use the dyn.load command which is part of the foreign interface capability. In fact it is the preferred way to do this since this will insure the compilation is done “under the supervision” of the R tools. However, instead of doing this compilation ourselves we could have allowed R to help us. It simply uses its input variables and ultimately sets an output variable. Note also that our routine doesn’t print/write things to output. Our goal is to generate a shared object file ( a “.so” file) that can be linked in to R. You should make sure, of course, that this code does compile correctly. This winds up being one of the more critical steps in the process. We also need to pay attention to the variable types as declared within the subroutine so we can match those types accordingly when calling the subroutine from R. So if you have some code that you want to bring in then you will need to embed that code within a subroutine definition. Fortran interface one must make reference to Fortran subroutines only – not Fortran functions or full on programs. And speaking of subroutines it is important to know that to use the. Next, I present a very simple Fortran 77 subroutine that computes the factorial of a number “n” and stashes the result into a variable called “answer”. , NAOK = FALSE, DUP = TRUE, PACKAGE, ENCODING) Lastly, it might simply be because your boss or faculty advisor is making you do it ! Whatever your reason(s) we’ll break the process of linking in Fortran code down into three general steps: 1) prepare the subroutine for compilation and generate a “shared object”, 2) load the shared object into an active R session, and 3) provide R variables to the shared object via the “.Fortran” call, which is part of the “Foreign Function Interface” within R.įunctions to make calls to compiled code that has been loaded into Perhaps they need to access subroutines from external Fortran libraries. Or maybe they have written some code in R that winds up being incredibly slow so they write a much faster version in Fortran and then want to call it from R. Most people wind up wanting to access Fortran from R for a few reasons such as they have some really fast and efficient Fortran code that they want to exploit within R. Additional Disclaimer: The timings I present in this post are based on an Apple MacBook OS level 10.9.2 with a 2.5 Ghz i5 processor and 4GB of RAM. I rarely use Windows though do know that the GNU suite is available for that OS so you should be able to link Fortran code into R there. Relative to operating systems I use Linux and OSX. I’ll talk about how to integrate Fortran code with R and, in a later post, discuss doing the same with C and C++.ĭISCLAIMER: To accomplish this work requires the presence of a working Fortran compiler such as the GNU suite of compilers (g77, gfortran, gcc, etc). This is true but until you are presented with a compelling use case you will most likely ignore such capability since you’ve already got plenty to do. And, along the way, you might have heard that R has the ability to “link in” code written in other languages such as C, C++, Fortran, and Java. ![]() If you are a newcomer to R then you are probably quite busy learning the semantics of the language as you experiment with the apply family of commands or come up to speed on the grouping and conditioning capabilities offered by lattice graphics.
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