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Sen
hi everyone,
I tried to run my code in RStudio,but I received this error message,what should
I do?
Error: cannot allocate vector of size 12.1 Gb
In addition: Warning messages:
1: In cor(coding.rpkm[grep("23.C", coding.rpkm$name), -1],
ncoding.rpkm[grep("23.C", :
Reached total allocation of 602
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
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.
I'm using Calloc from R.h. The prototype of the function is
type* Call
lement; that
> is the reason for the "doubling".
>
>
> On Mon, Jul 15, 2013 at 6:50 PM, ivo welch wrote:
>
>> dear R experts: I am curious again about R memory allocation strategies.
>> Consider an intentionally inefficient program:
>>
>> ranmatm
element; that
is the reason for the "doubling".
On Mon, Jul 15, 2013 at 6:50 PM, ivo welch wrote:
> dear R experts: I am curious again about R memory allocation strategies.
> Consider an intentionally inefficient program:
>
> ranmatme <- function( lx, rx ) {
> m &l
dear R experts: I am curious again about R memory allocation strategies.
Consider an intentionally inefficient program:
ranmatme <- function( lx, rx ) {
m <- matrix(NA, nrow=lx, ncol=rx)
for (li in 1:rx) {
cat("\tLag i=", li, "object size=", object.si
On 05/25/2012 06:29 AM, swaraj basu wrote:
Dear All,
I am running R in a system with the following configuration
*Processor: Intel(R) Xeon(R) CPU X5650 @ 2.67GHz
OS: Ubuntu X86_64 10.10
RAM: 24 GB*
The R session info is
*
R version 2.14.1 (2011-12-22)
Platform: x86_64-pc-linux-gnu (
Dear All,
I am running R in a system with the following configuration
*Processor: Intel(R) Xeon(R) CPU X5650 @ 2.67GHz
OS: Ubuntu X86_64 10.10
RAM: 24 GB*
The R session info is
*
R version 2.14.1 (2011-12-22)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8
Dear All,
I am running R in a system with the following configuration
*Processor: Intel(R) Xeon(R) CPU X5650 @ 2.67GHz
OS: Ubuntu X86_64 10.10
RAM: 24 GB*
The R session info is
*
R version 2.14.1 (2011-12-22)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8
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
Dear all, I know this problem was discussed many times in forum, however
unfortunately I could not find any way out for my own problem. Here I am
having Memory allocation problem while generating a lot of random number.
Here is my description:
> rnorm(5*6000)
Error: cannot allocate vector of s
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
p@r-project.org
>Subject: [R] memory allocation in R
>
>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
>s
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 workspace. If I then save the workspace, close R,
and open the wo
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
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 memory status in my pc I get
the following:
> memory.size()
[1] 676.3
> memory.siz
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
I would also like to include details on my R version
> version
_
platform x86_64-pc-mingw32
arch x86_64
os mingw32
system x86_64, mingw32
s
Hi R users
I am trying to run a non linear parameter optimization using the
function optim() and I have problems regarding memory allocation.
My data are in a dataframe with 9 columns. There are 656100 rows.
>head(org_results)
comb.id p H1 H2 Range Rep no.steps dist a
I forgot to mention that I am using windows 7 (64-bit) and the R version
2.11.1 (64-bit)
Thank you
Lorenzo
From: Lorenzo Cattarino
Sent: Wednesday, 3 November 2010 10:52 AM
To: r-help@r-project.org
Subject: memory allocation problem
Hi R users
I am trying to run a non linear
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
Hi Everyone,
I am getting the following error message
Error: cannot allocate vector of size 2.6 Gb
In addition: Warning messages:
1: In dim(res$res) = dim(bi) :
Reached total allocation of 8122Mb: see help(memory.size)
2: In dim(res$res) = dim(bi) :
Reached total allocation of 8122Mb: see hel
On Wed, Jul 14, 2010 at 05:51:17PM +0200, will.ea...@gmx.net wrote:
> Dear all,
>
> how can I use R on a 64-bit Windows Server 2003 machine (24GB RAM) with more
> than 3GB of working memory and make full use of it.
>
> I started R --max-mem-size=3G since I got the warning that larger values are
Dear all,
how can I use R on a 64-bit Windows Server 2003 machine (24GB RAM) with more
than 3GB of working memory and make full use of it.
I started R --max-mem-size=3G since I got the warning that larger values are
too large and ignored.
In R I got:
> memory.size(max=FALSE)
[1] 10.5
> memory
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
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 copies that can be problematic. I looked for a way t
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
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 vector of size 907.3 Mb
when i read the arc
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
Dear R users,
I am running a large loop over about 400 files. To outline generally,
the code reads in the initial data file, then uses lookup text files to
obtain more information before connecting to a SQL database using RODBC
and extracting more data. Finally all this is polar plotted.
My proble
Following code bugs with "Memory allocation failed: Copying Node" error after
parsing n thousand files. I have included the main code(below) and
functions(after the main code).
I am not sure which lines are causing the copying Node which results in
memory failure. Please advise.
#Beginning
Hello All,
I have a problem when I try and run an nlme model with an added correlation
structure on a large dataset. This is not surprising, but I am not sure how
to fix this problem. I am using R 2.6.1, and I have had similar problems in
S-plus.
My dataset is mass growth data from the same 8
Hello R-ill world!
My problem : I obtain a segmentation fault when passing a character
argument to a C function, compiled in a shared object and loaded by
dyn.load.
1. As manuals (and overall "Writing R extensions ") don't seem to
mention it or I failed to find the info, could someone explain
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