Thanks Brian, I stand corrected.
David Scott
On 27/02/2011 12:32 a.m., Prof Brian Ripley wrote:
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...@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
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_________________________________________________________________
David Scott Department of Statistics
The University of Auckland, PB 92019
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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.sc...@auckland.ac.nz, Fax: +64 9 373 7018
Director of Consulting, Department of Statistics
______________________________________________
R-help@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.
