[R] barplot, for loop?
Hi R-users, I have a dataset like this: kuvaaja kuva yhteispisteet Hannu isokala 8 Hannu kaapin alta löytynyt 2 Hannu kaapin alta löytynyt 2 8 Hannu limamikko 1 Hannu maukasta marmeladia 8 Hannu skrinnareita 4 Hate madekoukkujen suojelupyhimys 3 Hate matka aikaan joka ei enää palaa 3 Hate munat puoliks padassa 6 Hate pyynikki 2 Hate vailla armeerausta 2 Lassi ajatelkaa, jos Häntä ei olisikaan 2 Lassi elämän viiva 7 Lassi pedot 1 Lassi portsan kundi 3 Lauri hipö 3 Lauri jääpuut 5 Lauri kökar 3 Lauri lumipuu 9 Petteri harmaaleppä 5 Petteri viileä harakka 2 Teemu harppi 2 Teemu Homo sapiens angelus 3 Teemu kainostelua 1 Teemu pinnalla 5 Teemu portinvartija 6 Teemu puikot 1 Teemu verkkovaja 3 I have done this: pisteet.hannu - subset(pisteet.sum, kuvaaja == Hannu, select=c(kuva, yhteispisteet)) (pisteet.hannu - pisteet.hannu[rev(order(pisteet.hannu$yhteispisteet)),]) pisteet.lauri - subset(pisteet.sum, kuvaaja == Lauri, select=c(kuva, yhteispisteet)) (pisteet.lauri - pisteet.lauri[rev(order(pisteet.lauri$yhteispisteet)),]) pisteet.lassi - subset(pisteet.sum, kuvaaja == Lassi, select=c(kuva, yhteispisteet)) (pisteet.lassi - pisteet.lassi[rev(order(pisteet.lassi$yhteispisteet)),]) pisteet.teemu - subset(pisteet.sum, kuvaaja == Teemu, select=c(kuva, yhteispisteet)) (pisteet.teemu - pisteet.teemu[rev(order(pisteet.teemu$yhteispisteet)),]) pisteet.petteri - subset(pisteet.sum, kuvaaja == Petteri, select=c(kuva, yhteispisteet)) (pisteet.petteri - pisteet.petteri[rev(order(pisteet.petteri$yhteispisteet )),]) pisteet.hate - subset(pisteet.sum, kuvaaja == Hate, select=c(kuva, yhteispisteet)) (pisteet.hate - pisteet.hate[rev(order(pisteet.hate$yhteispisteet)),]) opar - par(mfrow=c(2,3), mar=c(11,3,3,3)) barplot(as.vector(pisteet.hannu$yhteispisteet), names.arg=as.vector(pisteet.hannu$kuva), las=3, cex.names=0.8, main=Hannu, ylim=c(0,10) ) barplot(as.vector(pisteet.lauri$yhteispisteet), names.arg=as.vector(pisteet.lauri$kuva), las=3, cex.names=0.8, main=Lauri, ylim=c(0,10) ) barplot(as.vector(pisteet.lassi$yhteispisteet), names.arg=as.vector(pisteet.lassi$kuva), las=3, cex.names=0.8, main=Lassi, ylim=c(0,10) ) barplot(as.vector(pisteet.teemu$yhteispisteet), names.arg=as.vector(pisteet.teemu$kuva), las=3, cex.names=0.8, main=Teemu, ylim=c(0,10) ) barplot(as.vector(pisteet.petteri$yhteispisteet), names.arg=as.vector(pisteet.petteri$kuva), las=3, cex.names=0.8, main=Petteri, ylim=c(0,10) ) barplot(as.vector(pisteet.hate$yhteispisteet), names.arg=as.vector(pisteet.hate$kuva), las=3, cex.names=0.8, main=Hate, ylim=c(0,10) ) par(opar) Queston is: how do I do this more effectively e.g. using for loop (without subsetting, straight from the original data)? Thanks in advance! -Lauri [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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.
Re: [R] barplot, for loop?
I put the data again because it looks like it went all mixed up. Data is named pisteet.sum. First row is the header row. kuvaaja kuva yhteispisteet Hannu isokala 8 Hannu kaapin alta löytynyt 2 Hannu kaapin alta löytynyt2 8 Hannu limamikko 1 Hannu maukasta marmeladia 8 Hannu skrinnareita 4 Hate madekoukkujen suojelupyhimys 3 Hate matka aikaan joka ei enää palaa 3 Hate munat puoliks padassa 6 Hate pyynikki 2 Hate vailla armeerausta 2 Lassi ajatelkaa, jos Häntä ei olisikaan 2 Lassi elämän viiva 7 Lassi pedot 1 Lassi portsan kundi 3 Lauri hipö 3 Lauri jääpuut 5 Lauri kökar 3 Lauri lumipuu 9 Petteri harmaaleppä 5 Petteri viileä harakka 2 Teemu harppi 2 Teemu Homo sapiens angelus 3 Teemu kainostelua 1 Teemu pinnalla 5 Teemu portinvartija 6 Teemu puikot 1 Teemu verkkovaja 3 10.3.2007 Lauri Nikkinen [EMAIL PROTECTED] kirjoitti: Hi R-users, -Lauri I have a dataset like this: kuvaaja kuva yhteispisteet Hannu isokala 8 Hannu kaapin alta löytynyt 2 Hannu kaapin alta löytynyt 2 8 Hannu limamikko 1 Hannu maukasta marmeladia 8 Hannu skrinnareita 4 Hate madekoukkujen suojelupyhimys 3 Hate matka aikaan joka ei enää palaa 3 Hate munat puoliks padassa 6 Hate pyynikki 2 Hate vailla armeerausta 2 Lassi ajatelkaa, jos Häntä ei olisikaan 2 Lassi elämän viiva 7 Lassi pedot 1 Lassi portsan kundi 3 Lauri hipö 3 Lauri jääpuut 5 Lauri kökar 3 Lauri lumipuu 9 Petteri harmaaleppä 5 Petteri viileä harakka 2 Teemu harppi 2 Teemu Homo sapiens angelus 3 Teemu kainostelua 1 Teemu pinnalla 5 Teemu portinvartija 6 Teemu puikot 1 Teemu verkkovaja 3 I have done this: pisteet.hannu - subset(pisteet.sum, kuvaaja == Hannu, select=c(kuva, yhteispisteet)) (pisteet.hannu - pisteet.hannu[rev(order(pisteet.hannu$yhteispisteet)),]) pisteet.lauri - subset(pisteet.sum, kuvaaja == Lauri, select=c(kuva, yhteispisteet)) (pisteet.lauri - pisteet.lauri[rev(order(pisteet.lauri$yhteispisteet)),]) pisteet.lassi - subset(pisteet.sum, kuvaaja == Lassi, select=c(kuva, yhteispisteet)) (pisteet.lassi - pisteet.lassi[rev(order(pisteet.lassi$yhteispisteet)),]) pisteet.teemu - subset(pisteet.sum, kuvaaja == Teemu, select=c(kuva, yhteispisteet)) (pisteet.teemu - pisteet.teemu[rev(order(pisteet.teemu$yhteispisteet)),]) pisteet.petteri - subset(pisteet.sum, kuvaaja == Petteri, select=c(kuva, yhteispisteet)) (pisteet.petteri - pisteet.petteri[rev(order( pisteet.petteri$yhteispisteet)),]) pisteet.hate - subset(pisteet.sum, kuvaaja == Hate, select=c(kuva, yhteispisteet)) (pisteet.hate - pisteet.hate[rev(order(pisteet.hate$yhteispisteet)),]) opar - par(mfrow=c(2,3), mar=c(11,3,3,3)) barplot(as.vector(pisteet.hannu$yhteispisteet), names.arg=as.vector(pisteet.hannu$kuva), las=3, cex.names=0.8, main=Hannu, ylim=c(0,10) ) barplot(as.vector(pisteet.lauri$yhteispisteet), names.arg=as.vector(pisteet.lauri$kuva), las=3, cex.names=0.8, main=Lauri, ylim=c(0,10) ) barplot(as.vector(pisteet.lassi$yhteispisteet), names.arg=as.vector(pisteet.lassi$kuva), las=3, cex.names=0.8, main=Lassi, ylim=c(0,10) ) barplot(as.vector(pisteet.teemu$yhteispisteet), names.arg=as.vector(pisteet.teemu$kuva), las=3, cex.names=0.8, main=Teemu, ylim=c(0,10) ) barplot(as.vector(pisteet.petteri$yhteispisteet), names.arg=as.vector(pisteet.petteri$kuva), las=3, cex.names=0.8, main=Petteri, ylim=c(0,10) ) barplot(as.vector(pisteet.hate$yhteispisteet), names.arg=as.vector(pisteet.hate$kuva), las=3, cex.names=0.8, main=Hate, ylim=c(0,10) ) par(opar) Queston is: how do I do this more effectively e.g. using for loop (without subsetting, straight from the original data)? Thanks in advance! -Lauri [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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.
Re: [R] Problem with ci.lmer() in package:gmodels
Hello Michael, I checked the source code, and the lower and upper confidence interval endpoints were simply reversed. The calculations themselves are correct. I have uploaded a new version of the gmodels package to the CRAN repository, and it should show up in a couple of days. In the mean time, you can either simply reverse them manually, or modify the source file est.lmer to swap the two endpoints. The new package also fixes the two places where my email address wasn't properly updated. -Greg From: Michael Kubovy kubovy_at_virginia.edu Date: Fri 09 Mar 2007 - 10:08:28 GMT Dear Friends, Please note that in the following CI lower CI higher: require(lmer) require(gmodels) fm2 - lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy) ci(fm2) Estimate CI lower CI upper Std. Error p-value (Intercept) 251.66693 266.06895 238.630280 7.056447 0 Days 10.52773 13.63372 7.389946 1.646900 0 _ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400Charlottesville, VA 22904-4400 Parcels:Room 102Gilmer Hall McCormick RoadCharlottesville, VA 22903 Office:B011+1-434-982-4729 Lab:B019+1-434-982-4751 Fax:+1-434-982-4766 WWW: http://www.people.virginia.edu/~mk9y/ R-help@stat.math.ethz.ch 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. __ R-help@stat.math.ethz.ch 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.
Re: [R] Using large datasets: can I overload the subscript operator?
On 3/9/07, Maciej Radziejewski [EMAIL PROTECTED] wrote: Hello, I do some computations on datasets that come from climate models. These data are huge arrays, significantly larger than typically available RAM, so they have to be accessed row-by-row, or rather slice-by slice, depending on the task. I would like to make an R package to easily access such datasets within R. The C++ backend is ready and being used under Windows/.Net/Visual Basic, but I have yet to learn the specifics of R programming to make a good R interface. I think it should be possible to make a package (call it slice) that could be used like this: library (slice) dataset - load.virtualarray (dataset_definition.xml) ordinaryvector - dataset [ , 2, 3] # Load a portion of the data from disk and extract it In the above dataset is an object that holds a definition of a 3-dimensional large dataset, and ordinaryvector is an ordinary R vector. The subscripting operator fetches necessary data from disk and extracts a required slice, taking care of caching and other technical details. So, my questions are: Has anyone ever made a similar extension, with virtual (lazy) arrays? Not quite the same but you might look at the g.data delayed data package in case its good enough for your needs. Note the dot. gdata without a dot is a different package. Can the suscript operator be overloaded like that in R? (I know it can be in S, at least for vectors.) Yes. You make your objects a class, myclass, and then define [.myclass - function... for myclass in the S3 class system and similarly in S4. S3 is easier to develop for and has higher performance so you probably want that rather than S4. A few examples packages are XML (see [.XMLNode), fame and zoo for S3 and 'its' for S4. Be sure to check out ?.subset See think post for context: http://tolstoy.newcastle.edu.au/R/devel/05/05/0853.html And a tough one: is it possible to make an expression like [1] (without quoutes) meaningful in R? At the moment it results in a syntax error. I would like to make it return an object of a special class that gets interpreted when subscripting my virtual array as drop this dimension, like this: dataset [, 2, 3, drop = F] # Return a 3-dimensional array dataset [, [2], 3, drop = F] # Return a 2-dimensional array dataset [, [2], [3], drop = F] # Return a 1-dimensional array, like dataset [, 2, 3] No but one idea is to define the single letter . (i.e. a dot) to be of a special class, dot say and define [.dot to produce objects of a special class (maybe also dot). Then you could write dataset[, .[2], .[3], drop = FALSE] if you define [.myclass to look for such objects. Another possibility is to use formula notation: dataset[, ~2, ~3, drop = FALSE] and have [.myclass handle formula arguments specially of perhaps forget about that notation and just extend drop: dataset[drop = 2:3] BTW, its better to use FALSE rather than F since F can be a variable name. __ R-help@stat.math.ethz.ch 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.
Re: [R] dendrogram - got it , just need to label :)
thx very much!
that helps to give those nodes somewhat dynamic names, so a legend to
explain those numbers would be a solution, i´ll think about.
Anyway, is it possible to name the nodes by hand, for example call
node1 myname1, node2 something else and so on ?
best
-m.
P.S.: Are there further packages you use for the dendrograms that you
could recommend ?
Am 10.03.2007 um 04:33 schrieb Steven McKinney:
local({
edgeLab - function(n) {
if(!is.leaf(n)) {
a - attributes(n)
i - i+1
attr(n, edgetext) -
format(i)
}
n
}
i - 0
})
dL - dendrapply(as.dendrogram(hclust(dist(iris[, 1:4]), method =
single)), edgeLab)
plot(dL)
[[alternative HTML version deleted]]
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[R] long character string problem
Hi All I am having 2 very long character strings (550chars) and I want to put them as expressions together with c(). The problem is that I also get these double-quotes, as seen below in 'fct'. How can I remove these double-quotes? I tried as.name() but it did not work (because of size?). These are creating trouble with subsequent programs, which I tested with strings that for some reason do not have these double quotes (see very bottom). Thanks Toby cum1 [1] A11*(X11*x1+X21*x2)+1*sqrt(B11*(X11*x1+X21*x2)^2+C11)A12*(X12*x1+X22*x2)+1*sqrt(B12*(X12*x1+X22*x2)^2+C12)A13*(X13*x1+X23*x2)+-1*sqrt(B13*(X13*x1+X23*x2)^2+C13)A14*(X14*x1+X24*x2)+-1*sqrt(B14*(X14*x1+X24*x2)^2+C14)A15*(X15*x1+X25*x2)+1*sqrt(B15*(X15*x1+X25*x2)^2+C15)A16*(X16*x1+X26*x2)+1*sqrt(B16*(X16*x1+X26*x2)^2+C16)A17*(X17*x1+X27*x2)+1*sqrt(B17*(X17*x1+X27*x2)^2+C17)A18*(X18*x1+X28*x2)+1*sqrt(B18*(X18*x1+X28*x2)^2+C18)A19*(X19*x1+X29*x2)+-1*sqrt(B19*(X19*x1+X29*x2)^2+C19)A110*(X110*x1+X210*x2)+1*sqrt(B110*(X110*x1+X210*x2)^2+C110) cum2 [1] A21*(X11*x1+X21*x2)+1*sqrt(B21*(X11*x1+X21*x2)^2+C21)A22*(X12*x1+X22*x2)+1*sqrt(B22*(X12*x1+X22*x2)^2+C22)A23*(X13*x1+X23*x2)+-1*sqrt(B23*(X13*x1+X23*x2)^2+C23)A24*(X14*x1+X24*x2)+-1*sqrt(B24*(X14*x1+X24*x2)^2+C24)A25*(X15*x1+X25*x2)+1*sqrt(B25*(X15*x1+X25*x2)^2+C25)A26*(X16*x1+X26*x2)+1*sqrt(B26*(X16*x1+X26*x2)^2+C26)A27*(X17*x1+X27*x2)+1*sqrt(B27*(X17*x1+X27*x2)^2+C27)A28*(X18*x1+X28*x2)+1*sqrt(B28*(X18*x1+X28*x2)^2+C28)A29*(X19*x1+X29*x2)+-1*sqrt(B29*(X19*x1+X29*x2)^2+C29)A210*(X110*x1+X210*x2)+1*sqrt(B210*(X110*x1+X210*x2)^2+C210) fct = c(as.expression(cum1), as.expression(cum2)) fct expression(A11*(X11*x1+X21*x2)+1*sqrt(B11*(X11*x1+X21*x2)^2+C11)A12*(X12*x1+X22*x2)+1*sqrt(B12*(X12*x1+X22*x2)^2+C12)A13*(X13*x1+X23*x2)+-1*sqrt(B13*(X13*x1+X23*x2)^2+C13)A14*(X14*x1+X24*x2)+-1*sqrt(B14*(X14*x1+X24*x2)^2+C14)A15*(X15*x1+X25*x2)+1*sqrt(B15*(X15*x1+X25*x2)^2+C15)A16*(X16*x1+X26*x2)+1*sqrt(B16*(X16*x1+X26*x2)^2+C16)A17*(X17*x1+X27*x2)+1*sqrt(B17*(X17*x1+X27*x2)^2+C17)A18*(X18*x1+X28*x2)+1*sqrt(B18*(X18*x1+X28*x2)^2+C18)A19*(X19*x1+X29*x2)+-1*sqrt(B19*(X19*x1+X29*x2)^2+C19)A110*(X110*x1+X210*x2)+1*sqrt(B110*(X110*x1+X210*x2)^2+C110), A21*(X11*x1+X21*x2)+1*sqrt(B21*(X11*x1+X21*x2)^2+C21)A22*(X12*x1+X22*x2)+1*sqrt(B22*(X12*x1+X22*x2)^2+C22)A23*(X13*x1+X23*x2)+-1*sqrt(B23*(X13*x1+X23*x2)^2+C23)A24*(X14*x1+X24*x2)+-1*sqrt(B24*(X14*x1+X24*x2)^2+C24)A25*(X15*x1+X25*x2)+1*sqrt(B25*(X15*x1+X25*x2)^2+C25)A26*(X16*x1+X26*x2)+1*sqrt(B26*(X16*x1+X26*x2)^2+C26)A27*(X17*x1+X27*x2)+1*sqrt(B27*(X17*x1+X27*x2)^2+C27)A28*(X18*x1+X28*x2)+1*sqrt(B28*(X18*x1+X28*x2)^2+C28)A29*(X19*x1+X29*x2)+-1*sqrt(B29*(X19*x1+X29*x2)^2+C29)A210*(X110*x1+X210*x2)+1*sqrt(B210*(X110*x1+X210*x2)^2+C210)) fct = c(expression(2*x1^3-7*x2^2-9), expression(x1^2-x2^3+1)) fct expression(2 * x1^3 - 7 * x2^2 - 9, x1^2 - x2^3 + 1) __ R-help@stat.math.ethz.ch 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.
[R] piecing together statements (macro?)
Hi All
I am pretty new to R but saw stata and sas's macro facilities and am looking
for
how such things work in R.
I am trying to piece together a series of statements:
n = 5 #want to have it dynamic with respect to n
for (j in 1:n) {
eval(paste(x, j, =x[, j, ], sep=))
}
I want the created statements 'x1=x[1]' immediately executed and tried to do
that with eval() but that did not work.
Any hints greatly appreciates.
Thanks Toby
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[R] Mac vs. PC
My adviser has a Mac notebook that he bought 6 months ago, and I have a PC notebook I bought a month ago. Here are the respective specs, as far as I know them: His: Mac OSX 1 GB DDR2 RAM Intel Core Duo, 2 GHz (2MB cache per core) Unknown HD Mine Windows Vista Home Premium 32bit 2 GB DDR2 RAM Intel Core 2 Duo, 2 GHz (4MB cache) 5400 RPM Hard Drive We are both running R. As a test to see whose laptop was faster, we decided to invert large random matrices. In R language, it looks like this: N=2000 A=rnorm(N^2) A=matrix(A,ncol=N) solve(A) This creates a matrix of 4,000,000 random normal deviates and inverts it. His computer takes about 7 seconds, while mine takes about 14. Why the difference? I have several working hypotheses, and it would be interesting to see what you guys think. 1. R on Mac was compiled with optimizations for the CPU, with R for Windows was not. I could test this by compiling R with the Intel compiler, or GCC with optimizations, and seeing if I get a significant speed boost. 2. His R is 64 bit, while mine is for 32 bit windows. (I'm not sure how much of a diference that makes, or whether OSX is 64 bit.) 3. Data is getting swapped to the hard drive, and my hard drive is slower than his. I chose a slower hard drive to get bigger capacity for the price. This is not intended to be an OMG MACOS = TEH R0X0R thread. I'm just trying to explain the discrepency. Thanks! __ R-help@stat.math.ethz.ch 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.
[R] useR! 2007 --- Call for papers and posters
R Users and Developers, The first North American useR! will be held at Iowa State University, Ames, Iowa, August 8–10, 2007. Information about the meeting can be found at http://www.user2007.org/. We are now ready to accept paper and poster submissions. Papers are encouraged in all areas, but particular emphasis is given to work describing newly created or improved R packages. Papers will be refereed and a best paper/presentation award is likely. Your full paper needs to be submitted by April 23, 5:00PM CST, to be considered for the meeting. There will also be the opportunity to present your work as a poster instead of a paper. Poster submissions will be in the form of an abstract and needs to be submitted by June 30. Submit full papers, and poster abstracts, to [EMAIL PROTECTED] useR! Program Committee [EMAIL PROTECTED] ___ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-announce __ R-help@stat.math.ethz.ch 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.
Re: [R] piecing together statements (macro?)
Read the FAQ 7.21:
http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html#How-can-I-turn-a-string-into-a-variable_003f
Note that it points out that you don't really want to do this anyways.
On 3/9/07, [EMAIL PROTECTED] [EMAIL PROTECTED] wrote:
Hi All
I am pretty new to R but saw stata and sas's macro facilities and am looking
for
how such things work in R.
I am trying to piece together a series of statements:
n = 5 #want to have it dynamic with respect to n
for (j in 1:n) {
eval(paste(x, j, =x[, j, ], sep=))
}
I want the created statements 'x1=x[1]' immediately executed and tried to do
that with eval() but that did not work.
Any hints greatly appreciates.
Thanks Toby
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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.
__
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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.
Re: [R] Mac vs. PC
Such a calculation would be dominated by the time spent inside a call to an offf-the-shelf C matrix inversion library used by R and is not really any test of R itself. On 3/9/07, Richard Morey [EMAIL PROTECTED] wrote: My adviser has a Mac notebook that he bought 6 months ago, and I have a PC notebook I bought a month ago. Here are the respective specs, as far as I know them: His: Mac OSX 1 GB DDR2 RAM Intel Core Duo, 2 GHz (2MB cache per core) Unknown HD Mine Windows Vista Home Premium 32bit 2 GB DDR2 RAM Intel Core 2 Duo, 2 GHz (4MB cache) 5400 RPM Hard Drive We are both running R. As a test to see whose laptop was faster, we decided to invert large random matrices. In R language, it looks like this: N=2000 A=rnorm(N^2) A=matrix(A,ncol=N) solve(A) This creates a matrix of 4,000,000 random normal deviates and inverts it. His computer takes about 7 seconds, while mine takes about 14. Why the difference? I have several working hypotheses, and it would be interesting to see what you guys think. 1. R on Mac was compiled with optimizations for the CPU, with R for Windows was not. I could test this by compiling R with the Intel compiler, or GCC with optimizations, and seeing if I get a significant speed boost. 2. His R is 64 bit, while mine is for 32 bit windows. (I'm not sure how much of a diference that makes, or whether OSX is 64 bit.) 3. Data is getting swapped to the hard drive, and my hard drive is slower than his. I chose a slower hard drive to get bigger capacity for the price. This is not intended to be an OMG MACOS = TEH R0X0R thread. I'm just trying to explain the discrepency. Thanks! __ R-help@stat.math.ethz.ch 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. __ R-help@stat.math.ethz.ch 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.
Re: [R] useR! 2007 --- Call for papers and posters
Di, You probably wanted to say first useR! (hosted) in North America, isn't that right? Anyway, I was wondering: what are the conditions for submitting a paper? Are the guidelines the same as JSS (or are they bringing it out)? If I can figure out how to make R packages, I might submit a paper on a package. Ranjan On Fri, 9 Mar 2007 15:26:24 -0600 Dianne Cook [EMAIL PROTECTED] wrote: R Users and Developers, The first North American useR! will be held at Iowa State University, Ames, Iowa, August 8___10, 2007. Information about the meeting can be found at http://www.user2007.org/. We are now ready to accept paper and poster submissions. Papers are encouraged in all areas, but particular emphasis is given to work describing newly created or improved R packages. Papers will be refereed and a best paper/presentation award is likely. Your full paper needs to be submitted by April 23, 5:00PM CST, to be considered for the meeting. There will also be the opportunity to present your work as a poster instead of a paper. Poster submissions will be in the form of an abstract and needs to be submitted by June 30. Submit full papers, and poster abstracts, to [EMAIL PROTECTED] useR! Program Committee [EMAIL PROTECTED] ___ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-announce __ R-help@stat.math.ethz.ch 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. __ R-help@stat.math.ethz.ch 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.
Re: [R] Off topic:Spam on R-help increase?
[Marc Schwartz] The Human Spam Filter (aka Martin) [...] The R mailing list has, indeed, be remarkably spam-free, and well-managed so far that I can see. I do hope, however, that Martin does not have to do the filtering himself -- it would be just daunting! In any case, Martin, a lot of thanks from me! -- François Pinard http://pinard.progiciels-bpi.ca __ R-help@stat.math.ethz.ch 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.
[R] RMySQL on win32
List, I just left an environment where I was running R and mysql on CENTOS. At the time of install, RMySQL was available on CRAN. Later installs on Ubuntu were possible because it was available as a package in the base repos. Now I'm in a new environment where I have no choice but to use Windows XP. I have just installed R 2.4.1 and MySQL 5.0.27. The installation instructions for getting RMySQL to install are a bit dense and possibly over my head, so I'm wondering if it is really necessary to compile the package against my current versions (yes, I realize that may be a question with a painfully obvious answer), or if I can simply use one of the precompiled binaries at David James's site. If anyone can tell me (or if there is a very easy way to get RMySQL up and running on win32), please let me know. As an aside, can anyone explain why it is not possible to keep that package in CRAN? I'm just curious about that, it's just for my own enlightenment. Thanks, Pete - Don't get soaked. Take a quick peek at the forecast [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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.
Re: [R] barplot, for loop?
Here is one way of doing it.
x - 'kuvaaja kuva yhteispisteet
Hannu isokala 8
Hannu kaapin alta löytynyt 2
Hannu kaapin alta löytynyt2 8
Hannu limamikko 1
Hannu maukasta marmeladia 8
Hannu skrinnareita 4
Hate madekoukkujen suojelupyhimys 3
Hate matka aikaan joka ei enää palaa 3
Hate munat puoliks padassa 6
Hate pyynikki 2
Hate vailla armeerausta 2
Lassi ajatelkaa, jos Häntä ei olisikaan 2
Lassi elämän viiva 7
Lassi pedot 1
Lassi portsan kundi 3
Lauri hipö 3
Lauri jääpuut 5
Lauri kökar 3
Lauri lumipuu 9
Petteri harmaaleppä 5
Petteri viileä harakka 2
Teemu harppi 2
Teemu Homo sapiens angelus 3
Teemu kainostelua 1
Teemu pinnalla 5
Teemu portinvartija 6
Teemu puikot 1
Teemu verkkovaja 3'
# read in the data
x.in - read.table(textConnection(x), header=TRUE)
# split data by groups
x.ku - split(x.in, x.in$kuvaaja)
# iterate through each group
for (i in names(x.ku)){
# sort the data in decending order
.order - rev(order(x.ku[[i]]$yhteispisteet))
# plot it
barplot(x.ku[[i]]$yhteispisteet[.order],
names.arg=as.character(x.ku[[i]]$kuva[.order]),
las=3,
cex.names=0.8,
main=i,
ylim=c(0,10)
)
}
On 3/10/07, Lauri Nikkinen [EMAIL PROTECTED] wrote:
Hi R-users,
I have a dataset like this:
kuvaaja
kuva
yhteispisteet
Hannu
isokala
8
Hannu
kaapin alta löytynyt
2
Hannu
kaapin alta löytynyt 2
8
Hannu
limamikko
1
Hannu
maukasta marmeladia
8
Hannu
skrinnareita
4
Hate
madekoukkujen suojelupyhimys
3
Hate
matka aikaan joka ei enää palaa
3
Hate
munat puoliks padassa
6
Hate
pyynikki
2
Hate
vailla armeerausta
2
Lassi
ajatelkaa, jos Häntä ei olisikaan
2
Lassi
elämän viiva
7
Lassi
pedot
1
Lassi
portsan kundi
3
Lauri
hipö
3
Lauri
jääpuut
5
Lauri
kökar
3
Lauri
lumipuu
9
Petteri
harmaaleppä
5
Petteri
viileä harakka
2
Teemu
harppi
2
Teemu
Homo sapiens angelus
3
Teemu
kainostelua
1
Teemu
pinnalla
5
Teemu
portinvartija
6
Teemu
puikot
1
Teemu
verkkovaja
3
I have done this:
pisteet.hannu - subset(pisteet.sum, kuvaaja == Hannu, select=c(kuva,
yhteispisteet))
(pisteet.hannu - pisteet.hannu[rev(order(pisteet.hannu$yhteispisteet)),])
pisteet.lauri - subset(pisteet.sum, kuvaaja == Lauri, select=c(kuva,
yhteispisteet))
(pisteet.lauri - pisteet.lauri[rev(order(pisteet.lauri$yhteispisteet)),])
pisteet.lassi - subset(pisteet.sum, kuvaaja == Lassi, select=c(kuva,
yhteispisteet))
(pisteet.lassi - pisteet.lassi[rev(order(pisteet.lassi$yhteispisteet)),])
pisteet.teemu - subset(pisteet.sum, kuvaaja == Teemu, select=c(kuva,
yhteispisteet))
(pisteet.teemu - pisteet.teemu[rev(order(pisteet.teemu$yhteispisteet)),])
pisteet.petteri - subset(pisteet.sum, kuvaaja == Petteri,
select=c(kuva,
yhteispisteet))
(pisteet.petteri - pisteet.petteri[rev(order(
pisteet.petteri$yhteispisteet
)),])
pisteet.hate - subset(pisteet.sum, kuvaaja == Hate, select=c(kuva,
yhteispisteet))
(pisteet.hate - pisteet.hate[rev(order(pisteet.hate$yhteispisteet)),])
opar - par(mfrow=c(2,3), mar=c(11,3,3,3))
barplot(as.vector(pisteet.hannu$yhteispisteet),
names.arg=as.vector(pisteet.hannu$kuva),
las=3,
cex.names=0.8,
main=Hannu,
ylim=c(0,10)
)
barplot(as.vector(pisteet.lauri$yhteispisteet),
names.arg=as.vector(pisteet.lauri$kuva),
las=3,
cex.names=0.8,
main=Lauri,
ylim=c(0,10)
)
barplot(as.vector(pisteet.lassi$yhteispisteet),
names.arg=as.vector(pisteet.lassi$kuva),
las=3,
cex.names=0.8,
main=Lassi,
ylim=c(0,10)
)
barplot(as.vector(pisteet.teemu$yhteispisteet),
names.arg=as.vector(pisteet.teemu$kuva),
las=3,
cex.names=0.8,
main=Teemu,
ylim=c(0,10)
)
barplot(as.vector(pisteet.petteri$yhteispisteet),
names.arg=as.vector(pisteet.petteri$kuva),
las=3,
cex.names=0.8,
main=Petteri,
ylim=c(0,10)
)
barplot(as.vector(pisteet.hate$yhteispisteet),
names.arg=as.vector(pisteet.hate$kuva),
las=3,
cex.names=0.8,
main=Hate,
ylim=c(0,10)
)
par(opar)
Queston is: how do I do this more effectively e.g. using for loop (without
subsetting, straight from the original data)? Thanks in advance!
-Lauri
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--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem you are trying to solve?
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Re: [R] Mac vs. PC
On Fri, 9 Mar 2007, Richard Morey wrote: 1. R on Mac was compiled with optimizations for the CPU, with R for Windows was not. I could test this by compiling R with the Intel compiler, or GCC with optimizations, and seeing if I get a significant speed boost. Yes. The Mac distribution uses Apple's linear algebra library, which is based on ATLAS and uses both cores. The default Windows distribution doesn't use an optimized linear algebra library because there isn't one built in to Windows. You can use ATLAS with the Windows distribution and there are even precompiled DLLs around somewhere. 2. His R is 64 bit, while mine is for 32 bit windows. (I'm not sure how much of a diference that makes, or whether OSX is 64 bit.) No. His R isn't 64bit. It would probably be slower if it were. The main reason to want 64bit R is to use lots of memory rather than to be fast. 3. Data is getting swapped to the hard drive, and my hard drive is slower than his. I chose a slower hard drive to get bigger capacity for the price. This could be true in principle, but I don't think the matrices are large enough for it to be the main factor. His computer won't be twice as fast on most R tasks (though it will still be twice as pretty, of course). -thomas Thomas Lumley Assoc. Professor, Biostatistics [EMAIL PROTECTED] University of Washington, Seattle __ R-help@stat.math.ethz.ch 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.
Re: [R] RMySQL on win32
Pete Cap wrote: List, I just left an environment where I was running R and mysql on CENTOS. At the time of install, RMySQL was available on CRAN. Later installs on Ubuntu were possible because it was available as a package in the base repos. Now I'm in a new environment where I have no choice but to use Windows XP. I have just installed R 2.4.1 and MySQL 5.0.27. The installation instructions for getting RMySQL to install are a bit dense and possibly over my head, so I'm wondering if it is really necessary to compile the package against my current versions (yes, I realize that may be a question with a painfully obvious answer), or if I can simply use one of the precompiled binaries at David James's site. If anyone can tell me (or if there is a very easy way to get RMySQL up and running on win32), please let me know. As an aside, can anyone explain why it is not possible to keep that package in CRAN? I'm just curious about that, it's just for my own enlightenment. For CRAN, I could only build against one version of MySQL for each version of R. In the past (particularly up to R-1.6.x), Brian Ripley made some bad experiences with incompatibilities when the package was built using different versions of MySQL. Hence we do not want to provide builds to the public that might only work together with some particular versions of MySQL. Best, Uwe Thanks, Pete - Don't get soaked. Take a quick peek at the forecast [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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. __ R-help@stat.math.ethz.ch 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.
Re: [R] Off topic:Spam on R-help increase?
On Sat, 2007-03-10 at 10:17 -0500, François Pinard wrote: [Marc Schwartz] The Human Spam Filter (aka Martin) [...] The R mailing list has, indeed, be remarkably spam-free, and well-managed so far that I can see. I do hope, however, that Martin does not have to do the filtering himself -- it would be just daunting! In any case, Martin, a lot of thanks from me! The comment was somewhat tongue-in-cheek. While a major proportion of spam can be filtered using automated tools, it takes a significant amount of manual effort to configure the tools to achieve the level of cleansing that we observe here. On my system (laptop running FC6 Linux), I am using SpamAssassin with Bayesian filtering enabled, along with remote spam checks such as DCC, Razor, Pyzor and some RBLs. I also recently started using FuzzyOCR (as a plug-in to SA) to enhance the filtering of spam containing only graphic content. These e-mails are of course specifically designed to obviate the utility of text based spam filtering. However, I still get some that come through despite the above. There are also 'borderline' e-mails that require manually running the spam/ham learning scripts. To increase the filtering effectiveness to the level we see here, I would have to spend a fair amount of time writing custom rules for SA and this is where I have no doubt, Martin spends a lot of his time with list management. HTH, Marc Schwartz __ R-help@stat.math.ethz.ch 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.
[R] finding max into matrix
Dear r-friends, Starting from a random position of a matrix, I would like find the position (index) of max values using 3x3 and 5x5 windows. Just supose that I have something like: set.seed(1) my.values-round(runif(441)*21,0) my.matrix-matrix(my.values,21) image(my.matrix,xaxs=r,yaxs=r,col=heat.colors(10)) start.pos-c(0.5,0.5) # this position are c(11,11) points(start.pos[1]~start.pos[2]) So I would like to see what are the values great than the value of my current position, and go for the position where the value are great. When the greatest value are present on more than one neighbour position, so I would like use a 5x5 window to decide how path could help me to maximize the value. From a random position, I will stop when no more values (using 3x3 and 5x5 windows) are great than the position that I reach up. I know that there are some GIS solutions that do this, but I really need use R to implement in a package that I am programing now. Kind regards, miltinho __ [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch 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.
[R] xtable with dupplicate rownames
I have a table (tab5; see below) with the first block showing the counts in a cross-tabulation, and the lower block reflecting the proportions of interest. tab5 None Low Level Moderate Intense Very Intense Total None 0.00 3.00 0.000.00 1.00 4 Low Level1.00 2.00 0.000.00 0.00 3 Moderate 2.00 3.00 2.000.00 0.00 7 Intense 3.00 1.00 1.001.00 0.00 6 Very Intense 0.00 1.00 2.000.00 0.00 3 Total6.00 10.00 5.001.00 1.0023 None 0.00 0.75 0.000.00 0.25 1 Low Level0.33 0.67 0.000.00 0.00 1 Moderate 0.29 0.43 0.290.00 0.00 1 Intense 0.50 0.17 0.170.17 0.00 1 Very Intense 0.00 0.33 0.670.00 0.00 1 When I execute foo5 - xtable(format(tab5), caption = XYZ) I get the following error message Warning message: some row.names duplicated: 7,8,9,10,11 -- row.names NOT used in: data.row.names(row.names, rowsi, i) Is there any way to force the duplicate row-names to be retained in xtable? Alternatively, is there a succinct way of building a cross-tabulation with both counts and proportions in each cell, and then using xtable? thanks for any and all tips Ani Anirudh V. S. Ruhil, Ph.D. Sr. Research Associate Voinovich Center for Leadership and Public Affairs Ohio University Building 21, The Ridges Athens, OH 45701-2979 Tel: 740.597.1949 | Fax: 740.597.3057 __ R-help@stat.math.ethz.ch 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.
Re: [R] Using large datasets: can I overload the subscript operator?
Maciej, I think it should be possible to make a package (call it slice) that could be used like this: ... Has anyone ever made a similar extension, with virtual (lazy) arrays? take a look at the filehash package at http://cran.r-project.org/doc/Rnews/Rnews_2006-4.pdf Regards, Rogerio __ R-help@stat.math.ethz.ch 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.
Re: [R] curve of density on histogram
On 08-Mar-07 Duncan Murdoch wrote:
On 3/8/2007 11:29 AM, (Ted Harding) wrote:
On 08-Mar-07 KOITA Lassana - STAC/ACE wrote:
[snip]
[snip]
The argument N to sdnorm is readily available from the argument x,
as N = length(x).
However, I cannot work out from the documentation for these panel
functions how to determine the width of the histogram bins, which
is argument binwid to sdnorm(). Hence I have simply set binwid=0.l0
to illustrate the point, since this gives an approximately correct
plot. But it will only be really correct when binwid can somehow
be determined from the hosyogram being plotted, and it is this
which I cannot see!
The breaks are one of the ... args passed to the panel function, so you
can get the binwidth from there. But there's another problem: the
panel.histogram function gives percent of total, so should integrate to
100, not to N. I think this version gives what is wanted:
library(lattice)
library(grid)
resp - rnorm(2000)
group - sample(c(G1, G2, G3, G4), replace = TRUE, size = 1000)
New function sdnorm:
sdnorm
-function(x,mean=0,sd=1,N=1,binwid=1){N*binwid*dnorm(x,mean,sd)}
histogram(~ resp | group, col=steelblue,
panel = function(x, ...){
std - if(length(x) 0) format(round(sd(x), 2), nsmall = 2) else
NA
n - length(x)
m - if(length(x) 0) format(round(mean(x), 2), nsmall = 2) else
NA
panel.histogram(x, ...)
breaks - list(...)$breaks
binwid - breaks[2]-breaks[1]
panel.mathdensity(dmath = sdnorm, col = green,
args =
list(mean=mean(x),sd=sd(x),N=100,binwid=breaks[2]-breaks[1]))
panel.abline(v= mean(x), col = red)
panel.abline(h=5)
panel.xyplot(x = jitter(x),type=p,pch=20,y = rep(0, length(x)),
col='yellow' )
x1 - unit(1, npc) - unit(2, mm)
y1 - unit(1, npc) - unit(2, mm)
grid.text(label = bquote(n == .(n)), x = x1, y = y1, just =
right)
grid.text(label = bquote(hat(m) == .(m)), x = x1, y = y1 - unit(1,
lines), just = right)
grid.text(label = bquote(hat(s) == .(std)), x = x1, y = y1 -
unit(2, lines), just = right)
})
Duncan, your statement that But there's another problem: the
panel.histogram function gives percent of total, so should integrate
to 100, not to N got me challenged -- there must be a work-round!
Finally I found it, but you have to make the change in (to me)
an unexpected place.
The following code (your code above, with two changed lines commented
out, and followed by the changed version) really does do the intended
job of plotting a panel of histograms of *counts* with the appropriate
scaled normal densities superimposed.
library(lattice)
library(grid)
N-2
resp - rnorm(N)
group - sample(c(G1, G2, G3, G4), replace = TRUE, size = N/4)
New function sdnorm:
sdnorm -function(x,mean=0,sd=1,N=1,binwid=1){N*binwid*dnorm(x,mean,sd)}
##Changed line
histogram(~ resp | group, col=steelblue,
histogram(~ resp | group, col=steelblue, type=count,
panel = function(x, ...){
std - if(length(x) 0) format(round(sd(x), 2), nsmall = 2) else
NA
n - length(x)
m - if(length(x) 0) format(round(mean(x), 2), nsmall = 2) else
NA
panel.histogram(x, ...)
breaks - list(...)$breaks
binwid - breaks[2]-breaks[1]
panel.mathdensity(dmath = sdnorm, col = green,
args =
## Changed line
list(mean=mean(x),sd=sd(x),N=100,binwid=breaks[2]-breaks[1]))
list(mean=mean(x),sd=sd(x),N=length(x),binwid=breaks[2]-breaks[1]))
panel.abline(v= mean(x), col = red)
panel.abline(h=5)
panel.xyplot(x = jitter(x),type=p,pch=20,y = rep(0, length(x)),
col='yellow' )
x1 - unit(1, npc) - unit(2, mm)
y1 - unit(1, npc) - unit(2, mm)
grid.text(label = bquote(n == .(n)), x = x1, y = y1, just = right)
grid.text(label = bquote(hat(m) == .(m)), x = x1, y = y1 - unit(1,
lines), just = right)
grid.text(label = bquote(hat(s) == .(std)), x = x1, y = y1 -
unit(2, lines), just = right)
})
I first tried setting type=count in the call to panel.histogram(),
as in
panel.histogram(x, type=count, ...)
but this got me an error message
Error in panel.histogram(x, type = count, ...) :
formal argument type matched by multiple actual arguments
from which I (slowly) deduced that it had already got that parameter
from somewhere else, after which it seemed natural that it got it
from the preceding call to
histogram(~ resp | group, col=steelblue,
[etc]
so I tried setting it there and (with the factor N-length(x) for
counts, instead of 100 for percentage) this worked!
(And I confess, when I posted my first suggestion, that I had
omitted to read the vertically aligned small print at the side
of the panel which said Percent of Total!).
Ah well, it's been an interesting little tour!
Thanks for the breakthrough, Duncan!
Ted.
E-Mail: (Ted Harding) [EMAIL PROTECTED]
Fax-to-email: +44
Re: [R] About cex=: how to improve resolution?
Use the symbols function! -Original Message- From: Luca Quaglia [EMAIL PROTECTED] To: r-help@stat.math.ethz.ch r-help@stat.math.ethz.ch Sent: 3/9/07 2:55 PM Subject: [R] About cex=: how to improve resolution? Hi, I need to plot a graph with a circle of radius 1 and with a series of points of different size. The size of these points compared to the fixed circle is important and bears a meaning. Here is the a simplified version of the code I'm using: x-seq(0,2,by=0.2) y-x z-seq(0,1,by=0.1) angle-pi/180*c(0:359) par(pty=s) plot(-2:2,-2:2,type=n) lines(cos(angle),sin(angle)) points(x,y,cex=z) I obtain points of the same size when cex=0.1/0.2/0.3/0.4 or cex=0.5/0.6/0.7 or cex=0.8/0.9/1.0. Please, does anyone know if there is a way of improving the resolution of cex in order to have 10 points *all* of different size (respecting the above written different values of cex)? The circle is fixed of radius 1 and the values of cex are in relation with that and they shouldn't be modified. Thanks, Luca __ R-help@stat.math.ethz.ch 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. __ R-help@stat.math.ethz.ch 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.
Re: [R] xtable with dupplicate rownames
I patched a solution together; essentially by using cbind to stack the proportions as columns. Duplicate columns names appear to pose no problems for xtable but duplicate rownames do! --On Saturday, March 10, 2007 1:11 PM -0500 Anirudh V. S. Ruhil [EMAIL PROTECTED] wrote: : I have a table (tab5; see below) with the first block showing the counts : in a cross-tabulation, and the lower block reflecting the proportions of : interest. : : tab5 : None Low Level Moderate Intense Very Intense Total : None 0.00 3.00 0.000.00 1.00 4 : Low Level1.00 2.00 0.000.00 0.00 3 : Moderate 2.00 3.00 2.000.00 0.00 7 : Intense 3.00 1.00 1.001.00 0.00 6 : Very Intense 0.00 1.00 2.000.00 0.00 3 : Total6.00 10.00 5.001.00 1.0023 : None 0.00 0.75 0.000.00 0.25 1 : Low Level0.33 0.67 0.000.00 0.00 1 : Moderate 0.29 0.43 0.290.00 0.00 1 : Intense 0.50 0.17 0.170.17 0.00 1 : Very Intense 0.00 0.33 0.670.00 0.00 1 : : When I execute : foo5 - xtable(format(tab5), caption = XYZ) : : I get the following error message : Warning message: : some row.names duplicated: 7,8,9,10,11 -- row.names NOT used in: : data.row.names(row.names, rowsi, i) : : Is there any way to force the duplicate row-names to be retained in : xtable? : : Alternatively, is there a succinct way of building a cross-tabulation : with both counts and proportions in each cell, and then using xtable? : : thanks for any and all tips : : Ani : : Anirudh V. S. Ruhil, Ph.D. : Sr. Research Associate : Voinovich Center for Leadership and Public Affairs : Ohio University : Building 21, The Ridges : Athens, OH 45701-2979 : Tel: 740.597.1949 | Fax: 740.597.3057 : : __ : R-help@stat.math.ethz.ch 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. Anirudh V. S. Ruhil, Ph.D. Sr. Research Associate Voinovich Center for Leadership and Public Affairs Ohio University Building 21, The Ridges Athens, OH 45701-2979 Tel: 740.597.1949 | Fax: 740.597.3057 __ R-help@stat.math.ethz.ch 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.
[R] Dyn.load and Unload problems
Hi, I am trying to modify the devX11.c source in the directory R-2.4.1/ src/modules/X11. Under OS X 10.4.9 running the R gui (R version 2.4.1) on a Powerbook, i type this and get the subsequent error. dyn.unload(/Library/Frameworks/R.framework/Resources/modules/ppc/ R_X11.so) Error in dyn.unload(x) : dynamic/shared library '/Library/Frameworks/ R.framework/Resources/modules/ppc/R_X11.so' was not loaded Yet, when i type the same line in terminal R, it works. Q1: How do find out what dlls have been loaded? Q2. In terminal R (with X11.app not running) , i unloaded R_X11.so (as above), which worked. I then loaded my own R_X11_b.so (displaying warning messages). I then unloaded this one and following occurred a) I ran X11() - it still ran, displaying my warnings - but it shouldn't have run since i unloaded all the R_X11.so (mine and R's) b)upon modifying the warning messages (again) and reloading, the warning messages don't reflect those of the new compiled devX11.c e.g in R_init_R_X11, which runs upon the so file being loaded, did not display the modified warning messages - it showed the old ones (in (a)) I would appreciate any help on this matter Rgds Saptarshi This R.version (identical for both the GUI and commandline versions) platform powerpc-apple-darwin8.8.0 arch powerpc os darwin8.8.0 system powerpc, darwin8.8.0 status major 2 minor 4.1 year 2006 month 12 day18 svn rev40228 language R version.string R version 2.4.1 (2006-12-18) __ R-help@stat.math.ethz.ch 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.
Re: [R] Mac vs. PC
2007/3/10, Richard Morey [EMAIL PROTECTED]: My adviser has a Mac notebook that he bought 6 months ago, and I have a PC notebook I bought a month ago. Here are the respective specs, as far as I know them: His: Mac OSX 1 GB DDR2 RAM Intel Core Duo, 2 GHz (2MB cache per core) Unknown HD Mine Windows Vista Home Premium 32bit 2 GB DDR2 RAM Intel Core 2 Duo, 2 GHz (4MB cache) 5400 RPM Hard Drive We are both running R. As a test to see whose laptop was faster, we decided to invert large random matrices. In R language, it looks like this: N=2000 A=rnorm(N^2) A=matrix(A,ncol=N) solve(A) This creates a matrix of 4,000,000 random normal deviates and inverts it. His computer takes about 7 seconds, while mine takes about 14. Why the difference? I have several working hypotheses, and it would be interesting to see what you guys think. 1. R on Mac was compiled with optimizations for the CPU, with R for Windows was not. I could test this by compiling R with the Intel compiler, or GCC with optimizations, and seeing if I get a significant speed boost. 2. His R is 64 bit, while mine is for 32 bit windows. (I'm not sure how much of a diference that makes, or whether OSX is 64 bit.) 3. Data is getting swapped to the hard drive, and my hard drive is slower than his. I chose a slower hard drive to get bigger capacity for the price. This is not intended to be an OMG MACOS = TEH R0X0R thread. I'm just trying to explain the discrepency. Thanks! __ R-help@stat.math.ethz.ch 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. Hi, For Windows you can check versions of Rblas.dll linked against the ATLAS library: http://cran.r-project.org/bin/windows/contrib/ATLAS/ Rod. __ R-help@stat.math.ethz.ch 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.
