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Sen
Ok, that is why i have suspected.
Thanks for the clear explanation.
[]s
Cassiano
2014-04-09 18:37 GMT-03:00 Peter Langfelder :
> On Wed, Apr 9, 2014 at 11:27 AM, Cassiano dos Santos
> wrote:
> > I am testing a call to a C function from R, using .C interface. The test
> > consists in passing
Cassiano dos Santos gmail.com> writes:
> I am testing a call to a C function from R, using .C interface. The test
> consists in passing a numeric vector to the C function with no entries,
> dynamically allocates n positions, makes attributions and return the
> vector to R.
Asking on StackOverflo
On Wed, Apr 9, 2014 at 11:27 AM, Cassiano dos Santos wrote:
> I am testing a call to a C function from R, using .C interface. The test
> consists in passing a numeric vector to the C function with no entries,
> dynamically allocates n positions, makes attributions and return the vector
> to R.
Wh
thx, jim. makes perfect sense now.
I guess a logical in R has a few million possible values ;-).
(Joke. I realize that 4 bytes is to keep the code convenient and faster.)
regards,
/iaw
Ivo Welch (ivo.we...@gmail.com)
On Mon, Jul 15, 2013 at 4:26 PM, jim holtman wrote:
> I can give you
I can give you the answer to #1. If you had put a "print(str(m))" you
would have seen that initially the matrix was setup as logical which
requires 4 bytes per element. On the first assignment of a numeric, the
mode of 'm' is changed to numeric which requires 8 bytes per element; that
is the reas
8-02-2012, 22:22 (+0545); Christofer Bogaso escriu:
> And the Session info is here:
>
> > sessionInfo()
> R version 2.14.0 (2011-10-31)
> Platform: i386-pc-mingw32/i386 (32-bit)
Not an expert, but I think that 32-bit applications can only address
up to 2GB on Windows.
--
Bye,
Ernest
_
32 bit windows has a memory limit of 2GB. Upgrading to a computer thats
less than 10 years old is the best path.
But short of that, if you're just generating random data, why not do it in
two or more pieces and combine them later?
mat.1 <- matrix(rnorm(5*2000),nrow=5)
mat.2 <- matrix(rno
On Nov 23, 2011, at 10:42 AM, Marc Jekel wrote:
> Dear R community,
>
> I was observing a memory issue in R (latest 64bit R version running on a win
> 7 64 bit system) that made me curious.
>
> I kept track of the memory f my PC allocated to R to calculate + keep several
> objects in the work
You may want to enable garbage collection on
gctorture(on = TRUE)
see: ?gctorture
?gcinfo
?object.size
>-Original Message-
>From: r-help-boun...@r-project.org
[mailto:r-help-boun...@r-project.org]
>On Behalf Of Marc Jekel
>Sent: 23 November 2011 15:42
>To: R-help@r-project.org
Hi Felipe,
On Fri, Apr 8, 2011 at 7:54 PM, Luis Felipe Parra
wrote:
> Hello, I am runnning a program on R with a "big" number of simulations and
> I am getting the following error:
>
> Error: no se puede ubicar un vector de tamaño 443.3 Mb
>
> I don't understand why because when I check the mem
Or do we, what's the word... imbue it."
- Jubal Early, Firefly
From:
Lorenzo Cattarino
To:
David Winsemius , Peter Langfelder
Cc:
r-help@r-project.org
Date:
11/03/2010 03:26 AM
Subject:
Re: [R] memory allocation problem
Sent by:
r-help-boun...@r-project.org
Thanks for all yo
help anyway
Lorenzo
-Original Message-
From: David Winsemius [mailto:dwinsem...@comcast.net]
Sent: Wednesday, 3 November 2010 12:48 PM
To: Lorenzo Cattarino
Cc: r-help@r-project.org
Subject: Re: [R] memory allocation problem
Restart your computer. (Yeah, I know that what the help-desk always
says.)
much appreciated
Lorenzo
-Original Message-
From: Lorenzo Cattarino
Sent: Wednesday, 3 November 2010 2:22 PM
To: 'David Winsemius'; 'Peter Langfelder'
Cc: r-help@r-project.org
Subject: RE: [R] memory allocation problem
Thanks for all your suggestions,
This is what I
Oops, I missed that you only have 4GB of memory... but since R is
apparently capable of using almost 10GB, either you actually have more
RAM, or the system is swapping some data to disk. Increasing memory
use in R might still help, but also may lead to a situation where the
system waits forever fo
Restart your computer. (Yeah, I know that what the help-desk always
says.)
Start R before doing anything else.
Then run your code in a clean session. Check ls() oafter starte up to
make sure you don't have a bunch f useless stuff in your .Rdata
file. Don't load anything that is not german
You have (almost) exhausted the 10GB you limited R to (that's what the
memory.size() tells you). Increase memory.limit (if you have more RAM,
use memory.limit(15000) for 15GB etc), or remove large data objects
from you session. Use rm(object), the issue garbage collection gc().
Sometimes garbage co
On 02.10.2010 03:10, Peter Langfelder wrote:
Hi Mete,
I think you should look at the help for memory.limit. Try to set a
higher one, for example
memory.limit(16000)
(I think 16GB is what xenon will take).
But not too funny given you have only 8Gb in your machine.
So the answer probably is
Hi Mete,
I think you should look at the help for memory.limit. Try to set a
higher one, for example
memory.limit(16000)
(I think 16GB is what xenon will take).
Peter
On Fri, Oct 1, 2010 at 6:02 PM, Mete Civelek wrote:
> Hi Everyone,
>
> I am getting the following error message
>
> Error: cann
Gabriel Margarido gmail.com> writes:
> ... I looked for a way to return the values
> without copying (even tried Rmemprof), but without success. Any ideas?
> ...
I solved similar problems using the R.oo package, which emulates
pass-by-reference semantics in 'R'.
HTH
Keith
On 1/16/2009 12:46 PM, Gabriel Margarido wrote:
Hello everyone,
I have the following issue: one function generates a very big array (can be
more than 1 Gb) and returns a few variables, including this big one. Memory
allocation is OK while the function is running, but the final steps make
some co
rami batal skrev:
> Dear all,
>
> I am trying to apply kmeans clusterring on a data file (size is about 300
> Mb)
>
> I read this file using
>
> x=read.table('file path' , sep=" ")
>
> then i do kmeans(x,25)
>
> but the process stops after two minutes with an error :
>
> Error: cannot allocate vect
Jamie Ledingham wrote:
becomes too much to handle by the time the loop reaches 170. Has anyone
had any experience of this problem before? Is it possible to 'wipe' R's
memory at the end of each loop - all results are plotted and saved or
written to text file at the end of each loop so this may b
See ?gc - it may help.
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Jamie Ledingham
Sent: Tuesday, August 12, 2008 9:16 AM
To: r-help@r-project.org
Subject: [R] Memory allocation problem
Dear R users,
I am running a large loop over about 400 files. To
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