[R] R in different OS

[Prof Brian Ripley]

It is less clear what you are after, but the canonical way to decide 
if your R session is on Windows is

.Platform$OS.type == "windows"

Unlike {R.}version$os and Sys.info()["sysname"], the set of values 
here is known and documented.  As ?R.version does say:

      Do _not_ use ‘R.version$os’ to test the platform the code is
      running on: use ‘.Platform$OS.type’ instead.  Slightly different
      versions of the OS may report different values of ‘R.version$os’,
      as may different versions of R.


On Sun, 27 Feb 2011, David Scott wrote:

> Not sure exactly what the  original poster was after, but for distinguishing 
> when I am working on different machines with different OS, I use something 
> like this:
>
> ### Set some state variables
> opSys <- Sys.info()["sysname"]
> if (opSys == "Windows"){
>  linux <- FALSE
> } else {
>  linux <- TRUE
> }
>
> David Scott
>
> On 26/02/2011 10:00 a.m., Ista Zahn wrote:
>> Hi,
>> 
>> see ?R.version
>> 
>> Something like
>> if(version$os == "mingw32") {
>>                 path = "/ABC"} else {
>>                 path = "/DEF"
>> }
>> 
>> might do it, but I'm not sure exactly what possible values version$os
>> can take or what determines the value exactly.
>> 
>> Best,
>> Ista
>> 
>> 
>> On Fri, Feb 25, 2011 at 1:23 PM, Hui Du<Hui.Du at dataventures.com>  wrote:
>>> Hi All,
>>>
>>>                 I have two Rs, one has been installed in Windows system 
>>> and another one has been installed under UNIX system. Is there any 
>>> environmental variable or function to tell me which R I am using? The 
>>> reason that I need to know it is under different system, the data path 
>>> could be different. I want to do something like
>>> 
>>> if it is R under Windows
>>>
>>>                 path = "/ABC"
>>> else if it is R under UNIX,
>>>                 path = "/DEF"
>>> 
>>> Any idea? Thanks.
>>> 
>>> Best Regards,
>>> 
>>> HXD
>>>
>>>         [[alternative HTML version deleted]]
>>> 
>>> ______________________________________________
>>> R-help at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide 
>>> http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>> 
>> 
>> 
>> 
>
>
> -- 
> _________________________________________________________________
> David Scott	Department of Statistics
> 		The University of Auckland, PB 92019
> 		Auckland 1142,    NEW ZEALAND
> Phone: +64 9 923 5055, or +64 9 373 7599 ext 85055
> Email:	d.scott at auckland.ac.nz,  Fax: +64 9 373 7018
>
> Director of Consulting, Department of Statistics
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595