Re: [R] Scaling of font sizes in layout()
Paul Murrell wrote:
Hi
Pisut Tempatarachoke wrote:
Hi all,
In the following example,
#--EXAMPLE--
test - function(subfigure)
{
plot(c(1:10),c(1:10),cex=4)
text(1,9,subfigure,cex=10)
}
m - matrix(c(1,2,5,5,3,4,5,5),4,2)
layout(m)
test(a)
test(b)
test(c)
test(d)
test(e)
#---
Is it possible to have the font (a,b,...,e) and pch sizes (including
the axis-label, tick and tick-label sizes) scaled proportionally with
the size of each plot when I put multiple plots on the same page?
When you have multiple figures, R tries to think for you and reduces the
base size of text. You can explicitly control this base size through
par(). Does the following slight modification of your example do what
you want?
test - function(subfigure)
{
plot(c(1:10),c(1:10),cex=4)
text(1,9,subfigure,cex=10)
}
m - matrix(c(1,2,5,5,3,4,5,5),4,2)
layout(m)
test(a)
test(b)
test(c)
test(d)
par(cex=1)
test(e)
Paul
Hi Paul,
Sorry for taking so long to reply. Your suggestion worked right away
but I have been busily caught up with other things. Again, thank you
very much for your help.
Best regards
Pisut
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RE: [R] memory limit problem
What do you mean `did not work'? Did it not start (you may need to reboot your machine to clear its memory tables) or did your task run out of memory? Please do read the posting guide and its references, and try to give useful information about the problem you encounter. Saying `did not work' without ever saying what is maximally uninformative. On Sun, 4 Apr 2004, Yi-Xiong Sean Zhou wrote: I tried using --max-mem-size=1400M at the command line on 1.8.1 and did not work. However, 1.9.0beta works. The Os is XP professional on Dell inspiron 8600. Yi-Xiong -Original Message- From: Prof Brian Ripley [mailto:[EMAIL PROTECTED] Sent: Saturday, April 03, 2004 11:20 PM To: Roger D. Peng Cc: Yi-Xiong Sean Zhou; [EMAIL PROTECTED] Subject: Re: [R] memory limit problem That is true, but I don't see that Yi-Xiong Sean Zhou has actually yet followed the instructions for 1.8.1, which is to set --max-mem-size on the command line (and this is in the rw-FAQ as people have pointed out). The issue is that on Windows the memory address space can get fragmented, and this is ameliorated by reserving memory in advance -- that is what using --max-mem-size (and not memory.limit) does for you. When used as recommended, both 1.8.1 and 1.9.0beta can handle workspaces of up to about 1.7Gb. 1.9.0 can go higher on suitable OSes: see its rw-FAQ. On Sun, 4 Apr 2004, Roger D. Peng wrote: In general, this is not an R problem, it is a Windows problem. I find that these types of memory problems do not appear on Linux, for example. -roger Yi-Xiong Sean Zhou wrote: R1.9.0beta solves the problem for now. The memory foot print of R1.9.0 is way smaller than R1.8.1, with only 400M. It will be interesting to see how R1.9.0 handles the memory problem when it needs more than 700M. Thanks for your helps. Yi-Xiong -Original Message- From: Roger D. Peng [mailto:[EMAIL PROTECTED] Sent: Saturday, April 03, 2004 2:52 PM To: Yi-Xiong Sean Zhou Cc: 'Uwe Ligges'; [EMAIL PROTECTED] Subject: Re: [R] memory limit problem You may want to try downloading the development version of R at http://cran.us.r-project.org/bin/windows/base/rdevel.html. This version deals with Windows' deficiencies in memory management a little better. -roger Yi-Xiong Sean Zhou wrote: After memory.limit(1500), the error message still pop out: Error: cannot allocate vector of size 11529 Kb While memory.size() [1] 307446696 memory.limit() [1] 1572864000 And the system is only using 723MB physical memory, while 2G is the total. Does anyone have a clue of what is going on? Yi-Xiong -Original Message- From: Uwe Ligges [mailto:[EMAIL PROTECTED] Sent: Saturday, April 03, 2004 12:40 PM To: Yi-Xiong Sean Zhou Cc: [EMAIL PROTECTED] Subject: Re: [R] memory limit problem Yi-Xiong Sean Zhou wrote: Could anyone advise me how to allocate 1.5Gbyte memory for R on a Dell laptop running XP professional with 2G memory? See ?Memory or the the R for Windows FAQ, which tells you: 2.7 There seems to be a limit on the memory it uses! Indeed there is. It is set by the command-line flag --max-mem-size (see How do I install R for Windows?) and defaults to the smaller of the amount of physical RAM in the machine and 1Gb. [...] I have tried C:\Program Files\R\rw1081\bin\Rgui.exe --max-vsize=1400M but I only get only 500MB for R actually. I also tried memory.limit(2^30) in R and got error of: Well, you don't want to allocate 2^30 *Mega*Bytes (see ?memory.limit), do you? Either use the command line flag --max-mem-size=1500M or within R: memory.limit(1500) Error in memory.size(size) : cannot decrease memory limit Since your limit was roughly 10^6-times off the right one, you got an integer overflow internally, I think. Uwe Ligges Yi-Xiong [[alternative HTML version deleted]] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford,
[R] Can't seem to finish a randomForest.... Just goes and goes!
Playing with randomForest, samples run fine. But on real data, no go. Here's the setup: OS X, same behavior whether I'm using R-Aqua 1.8.1 or the Fink compile-of-my-own with X-11, R version 1.8.1. This is on OS X 10.3 (aka Panther), G4 800Mhz with 512M physical RAM. I have not altered the Startup options of R. Data set is read in from a text file with read.table, and has 46 variables and 1,855 cases. Trying the following: The DV is categorical, 0 or 1. Most of the IV's are either continuous, or correctly read in as factors. The largest factor has 30 levels Only the DV seems to need identifying as a factor to force class trees over regresssion: Mydata$V46-as.factor(Mydata$V46) Myforest.rf-randomForest(V46~.,data=Mydata,ntrees=100,mtry=7,proximities=FALSE , importance=FALSE) 5 hours later, R.bin was still taking up 75% of my processor. When I've tried this with larger data, I get errors referring to the buffer (sorry, not in front of me right now). Any ideas on this? The data don't seem horrifically large. Seems like there are a few options for setting memory size, but I'm not sure which of them to try tweaking, or if that's even the issue. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
RE: [R] Can't seem to finish a randomForest.... Just goes and goe s!
When you have fairly large data, _do not use the formula interface_, as a couple of copies of the data would be made. Try simply: Myforest.rf - randomForest(Mydata[, -46], Mydata[,46], ntrees=100, mtry=7) [Note that you don't need to set proximity (not proximities) or importance to FALSE, as that's the default already.] You might also want to use do.trace=1 to see if trees are actually being grown (assuming there's no output buffering as in Rgui on Windows, otherwise you'll probably want to turn that off). I had run randomForest on data set much larger than that, without problem, so I don't imagine your data would be `difficult'. (I have not used the Mac, though.) Andy From: David L. Van Brunt, Ph.D. Playing with randomForest, samples run fine. But on real data, no go. Here's the setup: OS X, same behavior whether I'm using R-Aqua 1.8.1 or the Fink compile-of-my-own with X-11, R version 1.8.1. This is on OS X 10.3 (aka Panther), G4 800Mhz with 512M physical RAM. I have not altered the Startup options of R. Data set is read in from a text file with read.table, and has 46 variables and 1,855 cases. Trying the following: The DV is categorical, 0 or 1. Most of the IV's are either continuous, or correctly read in as factors. The largest factor has 30 levels Only the DV seems to need identifying as a factor to force class trees over regresssion: Mydata$V46-as.factor(Mydata$V46) Myforest.rf-randomForest(V46~.,data=Mydata,ntrees=100,mtry=7 ,proximities=FALSE , importance=FALSE) 5 hours later, R.bin was still taking up 75% of my processor. When I've tried this with larger data, I get errors referring to the buffer (sorry, not in front of me right now). Any ideas on this? The data don't seem horrifically large. Seems like there are a few options for setting memory size, but I'm not sure which of them to try tweaking, or if that's even the issue. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Can't seem to finish a randomForest.... Just goes and goe s!
Thanks for the pointer!! Can't believe you got back to me so quickly on a Sunday evening. I'll give that a shot and let you know how it goes. On 4/4/04 19:07, Liaw, Andy [EMAIL PROTECTED] wrote: When you have fairly large data, _do not use the formula interface_, as a couple of copies of the data would be made. Try simply: Myforest.rf - randomForest(Mydata[, -46], Mydata[,46], ntrees=100, mtry=7) [Note that you don't need to set proximity (not proximities) or importance to FALSE, as that's the default already.] You might also want to use do.trace=1 to see if trees are actually being grown (assuming there's no output buffering as in Rgui on Windows, otherwise you'll probably want to turn that off). I had run randomForest on data set much larger than that, without problem, so I don't imagine your data would be `difficult'. (I have not used the Mac, though.) Andy From: David L. Van Brunt, Ph.D. Playing with randomForest, samples run fine. But on real data, no go. Here's the setup: OS X, same behavior whether I'm using R-Aqua 1.8.1 or the Fink compile-of-my-own with X-11, R version 1.8.1. This is on OS X 10.3 (aka Panther), G4 800Mhz with 512M physical RAM. I have not altered the Startup options of R. Data set is read in from a text file with read.table, and has 46 variables and 1,855 cases. Trying the following: The DV is categorical, 0 or 1. Most of the IV's are either continuous, or correctly read in as factors. The largest factor has 30 levels Only the DV seems to need identifying as a factor to force class trees over regresssion: Mydata$V46-as.factor(Mydata$V46) Myforest.rf-randomForest(V46~.,data=Mydata,ntrees=100,mtry=7 ,proximities=FALSE , importance=FALSE) 5 hours later, R.bin was still taking up 75% of my processor. When I've tried this with larger data, I get errors referring to the buffer (sorry, not in front of me right now). Any ideas on this? The data don't seem horrifically large. Seems like there are a few options for setting memory size, but I'm not sure which of them to try tweaking, or if that's even the issue. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html -- Notice: This e-mail message, together with any attachments, contains information of Merck Co., Inc. (One Merck Drive, Whitehouse Station, New Jersey, USA 08889), and/or its affiliates (which may be known outside the United States as Merck Frosst, Merck Sharp Dohme or MSD and in Japan, as Banyu) that may be confidential, proprietary copyrighted and/or legally privileged. It is intended solely for the use of the individual or entity named on this message. If you are not the intended recipient, and have received this message in error, please notify us immediately by reply e-mail and then delete it from your system. -- -- David L. Van Brunt, Ph.D. Outlier Consulting Development mailto: [EMAIL PROTECTED] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Cochrane-Orcutt
hi everybody i'm looking for a function to estimate a regression model via the Cochrane Orcutt method thanks __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] memory limit problem
Do you mean in Linux, there is no need to set memory limit? If needed, how to set it? Thanks. From: Roger D. Peng [EMAIL PROTECTED] To: Yi-Xiong Sean Zhou [EMAIL PROTECTED] CC: [EMAIL PROTECTED] Subject: Re: [R] memory limit problem Date: Sun, 04 Apr 2004 00:13:46 -0500 In general, this is not an R problem, it is a Windows problem. I find that these types of memory problems do not appear on Linux, for example. -roger Yi-Xiong Sean Zhou wrote: R1.9.0beta solves the problem for now. The memory foot print of R1.9.0 is way smaller than R1.8.1, with only 400M. It will be interesting to see how R1.9.0 handles the memory problem when it needs more than 700M. Thanks for your helps. Yi-Xiong -Original Message- From: Roger D. Peng [mailto:[EMAIL PROTECTED] Sent: Saturday, April 03, 2004 2:52 PM To: Yi-Xiong Sean Zhou Cc: 'Uwe Ligges'; [EMAIL PROTECTED] Subject: Re: [R] memory limit problem You may want to try downloading the development version of R at http://cran.us.r-project.org/bin/windows/base/rdevel.html. This version deals with Windows' deficiencies in memory management a little better. -roger Yi-Xiong Sean Zhou wrote: After memory.limit(1500), the error message still pop out: Error: cannot allocate vector of size 11529 Kb While memory.size() [1] 307446696 memory.limit() [1] 1572864000 And the system is only using 723MB physical memory, while 2G is the total. Does anyone have a clue of what is going on? Yi-Xiong -Original Message- From: Uwe Ligges [mailto:[EMAIL PROTECTED] Sent: Saturday, April 03, 2004 12:40 PM To: Yi-Xiong Sean Zhou Cc: [EMAIL PROTECTED] Subject: Re: [R] memory limit problem Yi-Xiong Sean Zhou wrote: Could anyone advise me how to allocate 1.5Gbyte memory for R on a Dell laptop running XP professional with 2G memory? See ?Memory or the the R for Windows FAQ, which tells you: 2.7 There seems to be a limit on the memory it uses! Indeed there is. It is set by the command-line flag --max-mem-size (see How do I install R for Windows?) and defaults to the smaller of the amount of physical RAM in the machine and 1Gb. [...] I have tried C:\Program Files\R\rw1081\bin\Rgui.exe --max-vsize=1400M but I only get only 500MB for R actually. I also tried memory.limit(2^30) in R and got error of: Well, you don't want to allocate 2^30 *Mega*Bytes (see ?memory.limit), do you? Either use the command line flag --max-mem-size=1500M or within R: memory.limit(1500) Error in memory.size(size) : cannot decrease memory limit Since your limit was roughly 10^6-times off the right one, you got an integer overflow internally, I think. Uwe Ligges Yi-Xiong [[alternative HTML version deleted]] __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
RE: [R] Cochrane-Orcutt
Dear pnick, If you search the r-help archives, you'll see that some time ago I posted a Cochrane-Orcutt function. It's not clear to me, however, why you'd want to use this in preference to the gls function in the nlme package. I hope this helps, John -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of [EMAIL PROTECTED] Sent: Sunday, April 04, 2004 7:20 PM To: r Subject: [R] Cochrane-Orcutt hi everybody i'm looking for a function to estimate a regression model via the Cochrane Orcutt method thanks __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] residuals with missing values
hi: sorry to bother you all again. I am running a simple lm(y~x+z) regression, in which some of the observations are missing. Unfortunately, the residuals vector from the lm object omits all the missing values, which means that I cannot simply do residual diagnostics (e.g., plot(y,x)). Would it not make more sense to have the residuals propagate the missing values, so that the residuals are guaranteed to have the same length as the variables? Alternatively, maybe the residuals() function could do this instead. But the documentation is not clear: I had a similar situation, and Brian Ripley said to me: If you have missing data in your data frame and want residuals for all observations, you need to use na.action=na.exclude, not the default na.omit. -- Ajay Shah Consultant [EMAIL PROTECTED] Department of Economic Affairs http://www.mayin.org/ajayshah Ministry of Finance, New Delhi __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] boot question
x-rnorm(20) mean(x) [1] -0.2272851 results-boot(x,mean,R=5) What in the world am I missing?? See http://www.mayin.org/ajayshah/KB/R/statistics.html -- Ajay Shah Consultant [EMAIL PROTECTED] Department of Economic Affairs http://www.mayin.org/ajayshah Ministry of Finance, New Delhi __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] x-only zoom and pan?
Hello list, Could the following be done without too much grief...? Lets say I have two or three time series objects that I want to inspect visually. Each I would plot with a y-offset so they stack up. They share the same X scaling. The problem is that each is perhaps 100K values. Due to the large number of values, features of the data sets cannot be seen when all values are plotted. What would be nice is to plot a fraction of the X range (say 10%). This would be equivalent to zooming in the X direction. Then using a key (ideally an arrow key), shift the viewing frame right or left to effectively scroll through the data. So first you view 0-10%, then 10-20% and so forth. If necessary I can fabricate a vector with X values in it and plot(x,y) instead of as time series, if this makes it any easier. I am using a Windows version of R. Thanks, =Randy= R. Zelick email: [EMAIL PROTECTED] Department of Biology voice: 503-725-3086 Portland State University fax: 503-725-3888 mailing: P.O. Box 751 Portland, OR 97207 shipping: 1719 SW 10th Ave, Room 246 Portland, OR 97201 __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] x-only zoom and pan?
Could the following be done without too much grief...? It sounds possible, but there are already packages that deal with these issues. Some suggestions: 1) Use SVG plots, and Adobe's SVG Viewer plug-in for various web browsers. See the RSvgDevice package for details. 2) Use the Java graphics device - though under Windows, getting SJava working can be problematic. http://www.omegahat.org/RJavaDevice/ Cheers Jason __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] How to improve this code?
If I understand correctly, storelist and customerlist are two column matrices
of lat and long and you want all combos less than a certain distance apart
sorted by store and distance.
dd is the distance matrix of all pairs. We form this into a data frame of row
numbers (i.e. store numbers), column numbers (i.e. customer numbers) and
distances, subset that and then sort it. Then tapply seq to each group of
data from the same store to get ranks within stores.
Note that this forms some very large matrices if your data is large.
require(fields)
maxd - 100
dd - rdist.earth( storelist, customerlist, miles = F )
out - data.frame( store=c(row(dd)), cust=c(col(dd)), dist=c(dd) )[c(dd)maxd,]
out - out[ order( out$store, out$dist ),]
rk - c( unlist( tapply( out$store, out$store, function(x)seq(along=x) ) ) )
out - cbind( rank=rk, out )
Danny Heuman dsheuman at rogers.com writes:
:
: Hi all,
:
: I've got some functioning code that I've literally taken hours to
: write. My 'R' coding is getting better...it used to take days :)
:
: I know I've done a poor job of optimizing the code. In addition, I'm
: missing an important step and don't know where to put it.
:
: So, three questions:
:
: 1) I'd like the resulting output to be sorted on distance (ascending)
: and to have the 'rank' column represent the sort order, so that rank 1
: is the first customer and rank 10 is the 10th. Where do I do this?
:
: 2) Can someone suggest ways of 'optimizing' or improving the code?
: It's the only way I'm going to learn better ways of approaching R.
:
: 3) If there are no customers in the store's Trade Area, I'd like the
: output file have nothing written to it . How can I do that?
:
: All help is appreciated.
:
: Thanks,
:
: Danny
:
:
: *
: library(fields)
:
: #Format of input files: ID, LONGITUDE, LATITUDE
:
: #Generate Store List
: storelist - cbind(1:100, matrix(rnorm(100, mean = -60, sd = 3), ncol
: = 1),
:matrix(rnorm(100, mean = 50, sd = 3), ncol = 1))
:
: #Generate Customer List
: customerlist - cbind(1:1,matrix(rnorm(1, mean = -60, sd =
: 20), ncol = 1),
:matrix(rnorm(1, mean = 50, sd = 10), ncol = 1))
:
: #Output file
: outfile - c:\\output.txt
: outfilecolnames - c(rank,storeid,custid,distance)
: write.table(t(outfilecolnames), file = outfile, append=TRUE,
: sep=,,row.names=FALSE, col.names=FALSE)
:
: #Trade Area Size
: TAsize - c(100)
:
: custlatlon - customerlist[, 2:3]
:
: for(i in 1:length(TAsize)){
: for(j in 1:nrow(storelist)){
: cat(Store: , storelist[j], TA Size = , TAsize[i],
: \n)
:
: storelatlon - storelist[j, 2:3]
:
: whichval -
: which(rdist.earth(t(as.matrix(storelatlon)), as.matrix(custlatlon),
: miles=F) = TAsize[i])
:
: dist -
: as.data.frame(rdist.earth(t(as.matrix(storelatlon)),
: as.matrix(custlatlon), miles=F)[whichval])
:
: storetag -
: as.data.frame(cbind(1:nrow(dist),storelist[j,1]))
: fincalc -
: as.data.frame(cbind(1:nrow(dist),(customerlist[whichval,1]),rdist.earth(t
(as.matrix(storelatlon)),
: as.matrix(custlatlon), miles=F)[whichval]))
:
: combinedata - data.frame(storetag, fincalc)
:
: combinefinal - subset(combinedata, select= c(-1,-3))
:
: flush.console()
:
: write.table(combinefinal, file = outfile, append=TRUE,
: sep=,, col.names=FALSE)
: }
:
: }
:
: __
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:
:
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