[R] Problems with bilinear interpolation of a grid
Dear all, I'm having trouble interpolating a number of gridded datasets that I have. I'm quite new to R so any help/advice that can be offered would be much appreciated! Firstly I'll describe my dataset. The data is a grid of the planet at 1 degree spatial resolution, with each grid cell containing a value describing a particular variable (e.g. population density) for coordinate pairs. The dimensions of the grid are 360col x 180row. The x-coordinates of the values within the grid are longitudes (from -179.5(W) to 179.5(E)) and the y-coordinates of the grid values are latitudes (from 89.5(N) to -89.5(S)). What I want to do is convert this 1 degree dataset to a finer resolution of 0.5 degrees, thereby quadrupling the number of cells within the frame (i.e. convert to 720 x 360 grid). I wish to have longitudinal values ranging from -179.75 to 179.75 and latitudinal values from 89.75 to -89.75. I selected the 'interp.surface' function in the 'fields' package to do this as it provides bilinear interpolation from one grid to another. I have written the following code to try and carry out my interpolation... library(fields) x.mat - sprintf(%.2f, seq(from = -179.5, to = 179.5, length=360)) # longitude grid values y.mat - sprintf(%.2f, seq(from = 89.5, to = -89.5, length=180)) # latitude grid values z.mat - read.table(BF_200501.txt, colClasses=numeric) # dataset z.mat - data.matrix(z.mat) obj - list(x=x.mat, y=y.mat, z=z.mat) #Setting up new grid a.mat - sprintf(%.2f, seq(from = -179.75, to = 179.75, length = 720)) # longitude grid values b.mat - sprintf(%.2f, seq(from = 89.75, to = -89.75, length = 360)) # latitude grid values loc - make.surface.grid(list(x=a.mat, y=b.mat)) #Interpolation new - interp.surface(obj, loc) However I get the following error message: Error in x.new - min(x) : non-numeric argument to binary operator Can anyone explain what this error message means and why I am getting it? Or are there other more effective ways to perform the interpolation on this sort of dataset? Like I said I'm new to R so any advice will be gratefully received. Many thanks, Andy _ [[elided Hotmail spam]] [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Warning messages when using rbind
Hi, You seem to have a glitch in one file, testread12=read.table(Test100.txt, head = T) str(testread12) # Column131 is converted to a factor # $ Column131: Factor w/ 2920 levels --,-0.000122393,.. combining the second data set with this one will convert the new data into factor for this column but some (most) levels were not present in the first file. HTH, baptiste gug wrote: Hello, I have been using a very simple rbind approach (simple enough for me to understand) to combine data files within R. It seems to work fine, but then generates warning messages for reasons that I can't begin to understand. The text below shows the issue. testread12=read.table(C:/Files/Test100.txt, head = T) testread11=read.table(C:/Files/Test101.txt, head = T) testbind1=rbind(testread12,testread11) testbind2=rbind(testread11,testread12) The testrbind1 line generates the following message: Warning message: In `[-.factor`(`*tmp*`, ri, value = c(0.00557998, -0.058016069, : invalid factor level, NAs generated However the testrbind2 line works fine. Although the data in the files is different, the format (columns, etc) should be identical. The fact that it works in one order, but not the other, makes it very difficult for me to understand what the problem is. Files attached. Any suggestions gratefully received. Thanks, Guy Green http://www.nabble.com/file/p24130996/Test101.txt Test101.txt http://www.nabble.com/file/p24130996/Test100.txt Test100.txt -- _ Baptiste Auguié School of Physics University of Exeter Stocker Road, Exeter, Devon, EX4 4QL, UK Phone: +44 1392 264187 http://newton.ex.ac.uk/research/emag __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Help on qpcR package
I am using R on a Windows XP professional platform.
The following code is part of a bigger one
CODE
press=function(y,x){
library(qpcR)
models.press=numeric(0)
cat(\n)
dep=y
print(dep)
indep=log(x)
print(indep)
yfit=dep-PRESS(lm(dep~indep))[[2]]
cat(\n yfit\n)
print(yfit)
yfit.orig=yfit
presid=y-yfit.orig
press=sum(presid^2)
cat(\n)
cat(PRESS =,press,\n)
}
On the command R window I define
- Ignored:
x=c(12,24,13,11,23,10,9,17,11,14,18)
y=c(10,11,9,8,5,12,11,21,12,13,14)
then I load the press source code, I run it using the x and y values
defined before
and I get the following
press(x,y)
Loading required package: drc
Loading required package: alr3
Loading required package: lattice
Loading required package: magic
Loading required package: abind
Loading required package: MASS
Loading required package: nlme
Loading required package: plotrix
'drc' has been loaded.
Please cite R and 'drc' if used for a publication,
for references type 'citation()' and 'citation('drc')'.
Loading required package: gtools
Loading required package: gplots
Loading required package: gdata
Loading required package: caTools
Loading required package: bitops
Loading required package: grid
Attaching package: 'gplots'
The following object(s) are masked from package:plotrix :
plotCI
The following object(s) are masked from package:stats :
lowess
'qpcR' has been loaded.
Please cite R and the following if used for a publication:
Spiess AN, Feig C, Ritz
Highly accurate sigmoidal fitting of real-time PCR data by introducing
a parameter for asymmetry.
BMC Bioinformatics 2008, 29:221
or
Ritz C, Spiess AN. qpcR: an R package for sigmoidal model selection in
quantitative real-time polymerase chain reaction analysis.
Bioinformatics 2008, 24:1549-1551
Newest version always available at www.dr-spiess.de/qpcR.html.
Attaching package: 'qpcR'
The following object(s) are masked from package:gplots :
residplot
[1] 12 24 13 11 23 10 9 17 11 14 18
[1] 2.302585 2.397895 2.197225 2.079442 1.609438 2.484907 2.397895
3.044522 2.484907 2.564949 2.639057
Error in get(noquote(a)) : object 'dep' not found
The error reported, as I understand it, is that the object dep it is
not defined. Obviously, at least to me, it is defined.
If I declare the dep and indep objects on the command R window i. e.
dep=y
indep=x
and rerun the programme then it runs correctly and gives
press(x,y)
[1] 12 24 13 11 23 10 9 17 11 14 18
[1] 2.302585 2.397895 2.197225 2.079442 1.609438 2.484907 2.397895
3.044522 2.484907 2.564949 2.639057
yfit
[1] 13.764062 24.199292 15.804140 15.192045 32.465326 9.547579
9.845243 6.176015 10.521896 12.325493 14.931854
PRESS = 248.7043
Can anybody point out what's the problem?
Thanks in advance
K. Karakostas
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Re: [R] Problems with bilinear interpolation of a grid
Both from the code and the error message it appears that you are creating character matrices and unrealistically expecting a function designed for numeric input to accept those as arguments. ?sprintf It appears you are hoping that sprintf gets you something you desire, but to my eyes it looks entirely troublesome in this application. You should be able to report which line of code is provoking the error. I'm guessing it is: loc - make.surface.grid(list(x=a.mat, y=b.mat)) What happens when you just use numeric arguments? -- David. On Jun 21, 2009, at 1:33 PM, Andrew Aldersley wrote: Dear all, I'm having trouble interpolating a number of gridded datasets that I have. I'm quite new to R so any help/advice that can be offered would be much appreciated! Firstly I'll describe my dataset. The data is a grid of the planet at 1 degree spatial resolution, with each grid cell containing a value describing a particular variable (e.g. population density) for coordinate pairs. The dimensions of the grid are 360col x 180row. The x-coordinates of the values within the grid are longitudes (from -179.5(W) to 179.5(E)) and the y-coordinates of the grid values are latitudes (from 89.5(N) to -89.5(S)). What I want to do is convert this 1 degree dataset to a finer resolution of 0.5 degrees, thereby quadrupling the number of cells within the frame (i.e. convert to 720 x 360 grid). I wish to have longitudinal values ranging from -179.75 to 179.75 and latitudinal values from 89.75 to -89.75. I selected the 'interp.surface' function in the 'fields' package to do this as it provides bilinear interpolation from one grid to another. I have written the following code to try and carry out my interpolation... library(fields) x.mat - sprintf(%.2f, seq(from = -179.5, to = 179.5, length=360)) # longitude grid values y.mat - sprintf(%.2f, seq(from = 89.5, to = -89.5, length=180)) # latitude grid values z.mat - read.table(BF_200501.txt, colClasses=numeric) # dataset z.mat - data.matrix(z.mat) obj - list(x=x.mat, y=y.mat, z=z.mat) #Setting up new grid a.mat - sprintf(%.2f, seq(from = -179.75, to = 179.75, length = 720)) # longitude grid values b.mat - sprintf(%.2f, seq(from = 89.75, to = -89.75, length = 360)) # latitude grid values loc - make.surface.grid(list(x=a.mat, y=b.mat)) #Interpolation new - interp.surface(obj, loc) However I get the following error message: Error in x.new - min(x) : non-numeric argument to binary operator Can anyone explain what this error message means and why I am getting it? Or are there other more effective ways to perform the interpolation on this sort of dataset? Like I said I'm new to R so any advice will be gratefully received. Many thanks, Andy David Winsemius, MD Heritage Laboratories West Hartford, CT __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] help with installation of local gzip-ped packages
I was suggested to install two tar-red and gzip-ped packages that are not part of CRAN or BioConductors yet. I read the R manual about Administration and could only find a good description of how to install packages not canonically included in CRAN repository, on UNIX systems. I work on Linux/SuSE and Windows ... so I am stuck with such an installation. Any suggestion in very welcome. Thank you. Maura tutti i telefonini TIM! [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Roxygen to ignore a block of code?
For instance, I am trying to run Roxygen on: require( zoo ) # needed for time series setClass( zoo ) # lets S4 know about S3 class so we can use as an argument setClass( myClass, representation( .zoo=zoo ), prototype( 0, as.Date(1970-01-01) )) When I run this code through Roxygen, it warns: No name found for the following expression: require( zoo ) and generates zoo.Rd - I don't want any zoo.Rd to be generated - I am a user of the library, not an implementer. 1. How can I tell Roxygen NOT to generate zoo.Rd? 2. What do I do to prevent Roxygen from warning about: require( zoo ) ? Thx. - Ken -- View this message in context: http://www.nabble.com/Roxygen-to-ignore-a-block-of-code--tp24133293p24137672.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] AIC score
Dear All, I've been using step function to find me the best model.this basically works by using AIC score fucntion that is implemented on step(). The problem I'm facing with lots of variables on the model for example : step(lm(x1~x2,x3,x4,..x13)) sometimes gives me a warning message which is : AIC=- inf Coefficients: (Intercept) wnt3.values wnt6.values wnt10b.values wnt9a.values 2.3462 -0.4689 2.0730 1.2769 -0.2319 sfrp1.valueswnt5b.values sfrp1.1.valuessfrp5.values fzd5.1.values -0.2597 0.3150 0.3811 0.5926 -1.5567 fzd1.values fzd4.values fzd6.values fzd7.values fzd7.1.values 0.6459 -2.3016 0.3636 NA NA fzd8.values NA Warning message: attempting model selection on an essentially perfect fit is nonsense . which stops the search. Does this means that Residual Sum of Squares (RSS) equals to zero that makes AIC goes to -inf .And how would I overcome this problem.Can I for example find those that have strong correlation with x1 first and then use AIC score to find me the best model among them,. Regards Adel, [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Need help installing xts package
Hi! Take a look at this page: http://fawn.hsu-hh.de/~steuer/rpage.html The package you want to install ist called R-base-devel-*.rpm These packages are provided in opensuse's build service. Hope that helps Detlef On Sat, 20 Jun 2009 21:52:56 -0400 R_help Help rhelp...@gmail.com wrote: Hi, I am trying to install package xts. I am using OPENSUSE 11 64 bit. When I invoke: install.pacakges(xts,dependencies=T) I received a lot of ERROR: compilation failed for package errors when R tries to install xts dependencies. I do not understand this behavior. I notice one thing. It complains. ERROR: compilation failed for package 'Hmisc' ** Removing '/home/chibi/R/x86_64-unknown-linux-gnu-library/2.8/Hmisc' * Installing *source* package 'Design' ... ** libs WARNING: R include directory is empty -- perhaps need to install R-devel.rpm or similar Is it because I need R-devel.rpm? What is it? I search google around and cannot find any explanation. Thank you. adschai [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Wisely, and slow. They stumble that run fast. - Shakespeare __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] read.table error
Thank-you all for your reply. It turns out that there were both # characters and unbalanced quotes in the character fields that were creating problems for read.table. Putting in the options quote= and comment= in the read.table statment fixes the problem. On Fri, Jun 19, 2009 at 9:51 PM, jim holtmanjholt...@gmail.com wrote: Try comment.char='', quote='' You may have unbalanced quotes or comments (#) in your data. On Fri, Jun 19, 2009 at 5:50 PM, Forafo San ppv.g...@gmail.com wrote: Hello, I'm receiving an error on attempting to use the read.table() function to read in data from a tab-delimited file. The file has more than 60,000 rows with 94 tab-delimited columns. However, the error occurs on row 3 of the file: wl -read.table(sr003lines.tab, header=T, sep=\t) Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, : line 3 did not have 94 elements On receiving this error, I wrote a python script to go through the file to find rows with fewer than the 94 columns -- python finds that the first row with fewer than 94 columns is 1,706 -- much later than what R reports. R keeps running into this problem even with my python-massaged input file that I know for sure contains only rows with 94 columns. I also copied the first 4 rows of the input file into a separate file -- R isn't able to get past this problem. I examined the row (line 3) of the input file -- the only thing that's unique about this line is that it contains a long string (236 characters) in a column that in the previous rows was empty. Any chance that this sort of thing would cause R to run into a road block? Thanks, Premal P. Vora Associate Prof. Finance Penn State Harrisburg __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Jim Holtman Cincinnati, OH +1 513 646 9390 What is the problem that you are trying to solve? __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Incidence Function Model in R help
All: Though I am fairly new to R, I am trying to work my way through J Oksanen's Incidence Function Model in R and can't get past some error with my glm arguments. I'm getting through attach(amphimedon_compressa) plot(x.crd,y.crd,asp=1,xlab=Easting,ylab=Northing,pch=21,col=p+1,bg=5*p) d-dist(cbind(x.crd,y.crd)) alpha-1 edis-as.matrix(exp(-alpha*d)) diag(edis)-0 edis-sweep(edis,2,A,*) S-rowSums(edis[,p0]) mod-glm(p~offset(2*log(S))+log(A),family=binomial) before I get the error message Error: NA/NaN/Inf in foreign function call (arg 4) which is an argument concerning weights, an optional vector, whose choices are NULL or a numeric vector. When I define weights=1, I get Error in model.frame.default(formula = p ~ offset(2 * log(S)) + log(A), : variable lengths differ (found for '(weights)') and when I define weights=1, I get Error in weights = 1 : comparison (4) is possible only for atomic and list types Any suggestions? Thanks! Steve [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Saving output in an iterated function
Unfortunately my actual function is a bit more complicated than
ce=ce+be and does many transformations on the original vectors.
Maybe something like this better conveys what I am trying to do:
functM - function(eh,be,period,endPeriod){
period - period+1
ce - eh+be
de - (eh+be)^2
ee - ifelse(cede,de,ce)
{if (period endPeriod)
functM(ce,be,period,endPeriod)
else data.frame(eh,be,ce,de,ee,period)}
}
ones - c(1,1,1)
twos - c(2,2,2)
functM(ones,twos,0,4)
On Sun, Jun 21, 2009 at 10:59 AM, Gabor
Grothendieckggrothendi...@gmail.com wrote:
Try Reduce:
f - function(d, incr = 1) with(d,
data.frame(eh = ce, be, ce = ce + be, period = period + incr))
d - data.frame(ce = ones, be = twos, period = 0)
Reduce(f, init = d, x = rep(1, 4))
Reduce(f, init = d, x = rep(1, 4), accumulate = TRUE)
On Sun, Jun 21, 2009 at 9:06 AM, Economics Guyeconomics@gmail.com wrote:
# I have a function that takes a few vectors manipulates them and then
outputs a matrix of results:
funct1 - function(eh,be){
ce - eh+be
data.frame(eh,be,ce)
}
ones - c(1,1,1)
twos - c(2,2,2)
funct1(ones,twos)
# I would like to iterate it and save the results from each iteration.
I could of course write a loop but I would like to do this is the most
efficient way possible. The best I have come up with is this:
functM - function(eh,be,period,endPeriod){
period - period+1
ce - eh+be
{if (period endPeriod)
functM(ce,be,period,endPeriod)
else data.frame(eh,be,ce,period)}
}
ones - c(1,1,1)
twos - c(2,2,2)
functM(ones,twos,0,4)
# As you can see it only reports the results form the last iteration.
Here it is the 4th iteration, but if you change the last argument of
the previous run of functM, you can see that it will always report the
final matrix. How can I have it save/store/write the results of each
iteration. I do not care if it stacks it all into the same matrix or
if I have to write.csv each time. I just want to do it in the most
efficient way possible (the actual program will run for many many
iterations of large vectors.
# Thanks.
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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] Help on qpcR package
Endy BlackEndy wrote:
I am using R on a Windows XP professional platform.
The following code is part of a bigger one
CODE
press=function(y,x){
library(qpcR)
models.press=numeric(0)
cat(\n)
dep=y
print(dep)
indep=log(x)
print(indep)
yfit=dep-PRESS(lm(dep~indep))[[2]]
cat(\n yfit\n)
print(yfit)
yfit.orig=yfit
presid=y-yfit.orig
press=sum(presid^2)
cat(\n)
cat(PRESS =,press,\n)
}
On the command R window I define
- Ignored:
x=c(12,24,13,11,23,10,9,17,11,14,18)
y=c(10,11,9,8,5,12,11,21,12,13,14)
then I load the press source code, I run it using the x and y values
defined before
and I get the following
press(x,y)
Loading required package: drc
Loading required package: alr3
Loading required package: lattice
Loading required package: magic
Loading required package: abind
Loading required package: MASS
Loading required package: nlme
Loading required package: plotrix
'drc' has been loaded.
Please cite R and 'drc' if used for a publication,
for references type 'citation()' and 'citation('drc')'.
Loading required package: gtools
Loading required package: gplots
Loading required package: gdata
Loading required package: caTools
Loading required package: bitops
Loading required package: grid
Attaching package: 'gplots'
The following object(s) are masked from package:plotrix :
plotCI
The following object(s) are masked from package:stats :
lowess
'qpcR' has been loaded.
Please cite R and the following if used for a publication:
Spiess AN, Feig C, Ritz
Highly accurate sigmoidal fitting of real-time PCR data by introducing
a parameter for asymmetry.
BMC Bioinformatics 2008, 29:221
or
Ritz C, Spiess AN. qpcR: an R package for sigmoidal model selection in
quantitative real-time polymerase chain reaction analysis.
Bioinformatics 2008, 24:1549-1551
Newest version always available at www.dr-spiess.de/qpcR.html.
Attaching package: 'qpcR'
The following object(s) are masked from package:gplots :
residplot
[1] 12 24 13 11 23 10 9 17 11 14 18
[1] 2.302585 2.397895 2.197225 2.079442 1.609438 2.484907 2.397895
3.044522 2.484907 2.564949 2.639057
Error in get(noquote(a)) : object 'dep' not found
The error reported, as I understand it, is that the object dep it is
not defined. Obviously, at least to me, it is defined.
If I declare the dep and indep objects on the command R window i. e.
dep=y
indep=x
and rerun the programme then it runs correctly and gives
press(x,y)
[1] 12 24 13 11 23 10 9 17 11 14 18
[1] 2.302585 2.397895 2.197225 2.079442 1.609438 2.484907 2.397895
3.044522 2.484907 2.564949 2.639057
yfit
[1] 13.764062 24.199292 15.804140 15.192045 32.465326 9.547579
9.845243 6.176015 10.521896 12.325493 14.931854
PRESS = 248.7043
Can anybody point out what's the problem?
Thanks in advance
K. Karakostas
You really need to contact the package maintainers about this one.
Since your example is (a) not reproducible by us and (b) involves
a niche package (one for a very specific type of analysis), you're
probably not going to get much help here. My guess is that the
package is trying to do something clever with environments that
makes their function not work when it is called from inside another
function. You could try running your function code by hand (i.e.
not from within a function) and see if that makes a difference.
Ben Bolker
--
View this message in context:
http://www.nabble.com/Help-on-qpcR-package-tp24137125p24138743.html
Sent from the R help mailing list archive at Nabble.com.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Help on qpcR package
Endy BlackEndy wrote:
I am using R on a Windows XP professional platform.
The following code is part of a bigger one
CODE
press=function(y,x){
library(qpcR)
models.press=numeric(0)
cat(\n)
dep=y
print(dep)
indep=log(x)
print(indep)
yfit=dep-PRESS(lm(dep~indep))[[2]]
cat(\n yfit\n)
print(yfit)
yfit.orig=yfit
presid=y-yfit.orig
press=sum(presid^2)
cat(\n)
cat(PRESS =,press,\n)
}
On the command R window I define
- Ignored:
x=c(12,24,13,11,23,10,9,17,11,14,18)
y=c(10,11,9,8,5,12,11,21,12,13,14)
then I load the press source code, I run it using the x and y values
defined before
and I get the following
press(x,y)
Loading required package: drc
Loading required package: alr3
Loading required package: lattice
Loading required package: magic
Loading required package: abind
Loading required package: MASS
Loading required package: nlme
Loading required package: plotrix
'drc' has been loaded.
Please cite R and 'drc' if used for a publication,
for references type 'citation()' and 'citation('drc')'.
Loading required package: gtools
Loading required package: gplots
Loading required package: gdata
Loading required package: caTools
Loading required package: bitops
Loading required package: grid
Attaching package: 'gplots'
The following object(s) are masked from package:plotrix :
plotCI
The following object(s) are masked from package:stats :
lowess
'qpcR' has been loaded.
Please cite R and the following if used for a publication:
Spiess AN, Feig C, Ritz
Highly accurate sigmoidal fitting of real-time PCR data by introducing
a parameter for asymmetry.
BMC Bioinformatics 2008, 29:221
or
Ritz C, Spiess AN. qpcR: an R package for sigmoidal model selection in
quantitative real-time polymerase chain reaction analysis.
Bioinformatics 2008, 24:1549-1551
Newest version always available at www.dr-spiess.de/qpcR.html.
Attaching package: 'qpcR'
The following object(s) are masked from package:gplots :
residplot
[1] 12 24 13 11 23 10 9 17 11 14 18
[1] 2.302585 2.397895 2.197225 2.079442 1.609438 2.484907 2.397895
3.044522 2.484907 2.564949 2.639057
Error in get(noquote(a)) : object 'dep' not found
The error reported, as I understand it, is that the object dep it is
not defined. Obviously, at least to me, it is defined.
If I declare the dep and indep objects on the command R window i. e.
dep=y
indep=x
and rerun the programme then it runs correctly and gives
press(x,y)
[1] 12 24 13 11 23 10 9 17 11 14 18
[1] 2.302585 2.397895 2.197225 2.079442 1.609438 2.484907 2.397895
3.044522 2.484907 2.564949 2.639057
yfit
[1] 13.764062 24.199292 15.804140 15.192045 32.465326 9.547579
9.845243 6.176015 10.521896 12.325493 14.931854
PRESS = 248.7043
Can anybody point out what's the problem?
Thanks in advance
K. Karakostas
You really need to contact the package maintainers about this one.
Since your example is (a) not reproducible by us and (b) involves
a niche package (one for a very specific type of analysis), you're
probably not going to get much help here. My guess is that the
package is trying to do something clever with environments that
makes their function not work when it is called from inside another
function. You could try running your function code by hand (i.e.
not from within a function) and see if that makes a difference.
Ben Bolker
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Re: [R] [Rd] Floating point precision / guard digits? (PR#13771)
Stavros Macrakis wrote [...] programming languages (including R). I don't know whether R's sum function uses this technique or some other (e.g. Kahan summation), but it does manage to give higher precision than summation with individual arithmetic operators: sum(c(2^63,1,-2^63)) = 1 not if the arguments are passed as separate elements in ...: x = c(2^63, 1, -2^63) sum(x) # 1 do.call(sum, as.list(x)) # 0 y = 1:3 sum(y) # 6 do.call(sum, as.list(y)) # 6 vQ __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Saving output in an iterated function
Extend it like this:
Try this:
f - function(d, endPeriod) with(d, {
period - period + 1
ce - eh + be
de - (eh + be)^2
ee - ifelse(ce de, de, ce)
eh - ifelse(period endPeriod, ce, eh)
data.frame(eh, be, ce, de, ee, period)
})
ones - c(1, 1, 1)
twos - c(2, 2, 2)
d - data.frame(eh = ones, be = twos, period = 0)
Reduce(f, init = d, x = rep(4, 4))
Reduce(f, init = d, x = rep(4, 4), accumulate = TRUE)
On Sun, Jun 21, 2009 at 4:49 PM, Economics Guyeconomics@gmail.com wrote:
Unfortunately my actual function is a bit more complicated than
ce=ce+be and does many transformations on the original vectors.
Maybe something like this better conveys what I am trying to do:
functM - function(eh,be,period,endPeriod){
period - period+1
ce - eh+be
de - (eh+be)^2
ee - ifelse(cede,de,ce)
{if (period endPeriod)
functM(ce,be,period,endPeriod)
else data.frame(eh,be,ce,de,ee,period)}
}
ones - c(1,1,1)
twos - c(2,2,2)
functM(ones,twos,0,4)
On Sun, Jun 21, 2009 at 10:59 AM, Gabor
Grothendieckggrothendi...@gmail.com wrote:
Try Reduce:
f - function(d, incr = 1) with(d,
data.frame(eh = ce, be, ce = ce + be, period = period + incr))
d - data.frame(ce = ones, be = twos, period = 0)
Reduce(f, init = d, x = rep(1, 4))
Reduce(f, init = d, x = rep(1, 4), accumulate = TRUE)
On Sun, Jun 21, 2009 at 9:06 AM, Economics Guyeconomics@gmail.com
wrote:
# I have a function that takes a few vectors manipulates them and then
outputs a matrix of results:
funct1 - function(eh,be){
ce - eh+be
data.frame(eh,be,ce)
}
ones - c(1,1,1)
twos - c(2,2,2)
funct1(ones,twos)
# I would like to iterate it and save the results from each iteration.
I could of course write a loop but I would like to do this is the most
efficient way possible. The best I have come up with is this:
functM - function(eh,be,period,endPeriod){
period - period+1
ce - eh+be
{if (period endPeriod)
functM(ce,be,period,endPeriod)
else data.frame(eh,be,ce,period)}
}
ones - c(1,1,1)
twos - c(2,2,2)
functM(ones,twos,0,4)
# As you can see it only reports the results form the last iteration.
Here it is the 4th iteration, but if you change the last argument of
the previous run of functM, you can see that it will always report the
final matrix. How can I have it save/store/write the results of each
iteration. I do not care if it stacks it all into the same matrix or
if I have to write.csv each time. I just want to do it in the most
efficient way possible (the actual program will run for many many
iterations of large vectors.
# Thanks.
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Re: [R] correlation between categorical data
At 07:40 21.06.2009, J Dougherty wrote: [...] There are other ways of regarding the FET. Since it is precisely what it says - an exact test - you can argue that you should avoid carrying over any conclusions drawn about the small population the test was applied to and employing them in a broader context. In so far as the test is concerned, the sample data and the contingency table it is arrayed in are the entire universe. In that sense, the FET can't be conservative or liberal. It isn't actually a hypothesis test and should not be thought of as one or used in the place of one. JDougherty Could you give some reference, supporting this, for me, surprising view? I don't see a necessary connection between an exact test and the idea that it does not test a hypothesis. Thanks, Heinz __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Incidence Function Model in R help
On Jun 21, 2009, at 2:47 PM, steve kimble wrote: All: Though I am fairly new to R, I am trying to work my way through J Oksanen's Incidence Function Model in R and can't get past some error with my glm arguments. I'm getting through attach(amphimedon_compressa) plot(x.crd,y.crd,asp=1,xlab=Easting,ylab=Northing,pch=21,col=p +1,bg=5*p) d-dist(cbind(x.crd,y.crd)) alpha-1 edis-as.matrix(exp(-alpha*d)) diag(edis)-0 That line may be unnecessary. I think as.matrix already did that: x - matrix(rnorm(9), nrow=3) m - as.matrix(dist(x)) m 123 1 0.00 3.287444 2.271032 2 3.287444 0.00 2.459300 3 2.271032 2.459300 0.00 edis-sweep(edis,2,A,*) S-rowSums(edis[,p0]) mod-glm( p~offset(2*log(S)) + log(A), family=binomial) before I get the error message Error: NA/NaN/Inf in foreign function call (arg 4) Can't you see that asking people to guess what might be the problem when the data is left as an unknown is an unreasonable request. This part of the Standard Message ... PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ... means that not just the commands but also data need to be provided, either as a toy dataset, or a small sample, or at a location where it can be accessed. which is an argument concerning weights, an optional vector, whose choices are NULL or a numeric vector. When I define weights=1, I get Error in model.frame.default(formula = p ~ offset(2 * log(S)) + log(A), : variable lengths differ (found for '(weights)') Just a guess, weights needs to be as long as the other vectors being given to the model? and when I define weights=1, I get That one is easy. You are using a comparison operator =, thinking it is the assignment operator - Error in weights = 1 : comparison (4) is possible only for atomic and list types Any suggestions? Thanks! Steve David Winsemius, MD Heritage Laboratories West Hartford, CT __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] rbind
Hi, I have a array like this data: 1 5 2 2342 3 33 and another data1: 1 6 2 5 3 7 when I do rbind(data,data1) I get not what I want they become 1 5 2 2342 3 33 101 6 102 5 103 7 but I want to make the index as increasing one by one. like 1 .. 2 .. 3 .. 4 .. 5 .. 6 .. So what command I should use thank you. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] deal with array row by row
because the index in the result of rebind is not increasing one by one, how can I deal with row one after another [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] rbind
You need to provide a reproducible example. At least provide an 'str' of your data and preferably the output of 'dput'. I am not sure what you data looks like. works fine for me when using matrices: data [,1] [1,]5 [2,] 2342 [3,] 33 data1 [,1] [1,]6 [2,]5 [3,]7 rbind(data,data1) [,1] [1,]5 [2,] 2342 [3,] 33 [4,]6 [5,]5 [6,]7 On Sun, Jun 21, 2009 at 8:31 PM, Xiaogang Yang gavinxy...@gmail.com wrote: Hi, I have a array like this data: 1 5 2 2342 3 33 and another data1: 1 6 2 5 3 7 when I do rbind(data,data1) I get not what I want they become 1 5 2 2342 3 33 101 6 102 5 103 7 but I want to make the index as increasing one by one. like 1 .. 2 .. 3 .. 4 .. 5 .. 6 .. So what command I should use thank you. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.htmlhttp://www.r-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Jim Holtman Cincinnati, OH +1 513 646 9390 What is the problem that you are trying to solve? [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] deal with array row by row
You need to indicate what the data is. You still reference the rows sequentially regardless of what that first column of your output is saying. PLEASE do read the posting guide http://www.R-project.org/posting-guide.htmlhttp://www.r-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Customize axis labels in xyplot
On Sat, Jun 20, 2009 at 9:13 AM, nmsetnm...@netcourrier.com wrote:
Hello,
I'm plotting an xyplot where a continuous var recorded every min is plotted
on y, and time expressed as HH:MM:SS on x, as follows :
xaxis=list(tick.number=12,rot=90)
lst=list(x=xaxis)
xyplot(upt$LOAD_1 ~ upt$TIME, data=upt, type=c('g','p', 'r'), scales=lst)
On the x-axis, every time label is drawn and the label quickly become
unreadable as they overlap on each other.
I wished to limit the number of label with 'tick.number=12' but it does not
work as the x values are not treated as a numerical sequence.
How can I limit the number of ticks and labels for a time series expressed
as HH:MM:SS ?
One way might be to convert to mins from an origin, the result would be less
expressive though.
A reproducible example would help. Have you tried using a date-time class?
-Deepayan
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and provide commented, minimal, self-contained, reproducible code.
[R] Saving output in an iterated function
# I have a function that takes a few vectors manipulates them and then
outputs a matrix of results:
funct1 - function(eh,be){
ce - eh+be
data.frame(eh,be,ce)
}
ones - c(1,1,1)
twos - c(2,2,2)
funct1(ones,twos)
# I would like to iterate it and save the results from each iteration.
I could of course write a loop but I would like to do this is the most
efficient way possible. The best I have come up with is this:
functM - function(eh,be,period,endPeriod){
period - period+1
ce - eh+be
{if (period endPeriod)
functM(ce,be,period,endPeriod)
else data.frame(eh,be,ce,period)}
}
ones - c(1,1,1)
twos - c(2,2,2)
functM(ones,twos,0,4)
# As you can see it only reports the results form the last iteration.
Here it is the 4th iteration, but if you change the last argument of
the previous run of functM, you can see that it will always report the
final matrix. How can I have it save/store/write the results of each
iteration. I do not care if it stacks it all into the same matrix or
if I have to write.csv each time. I just want to do it in the most
efficient way possible (the actual program will run for many many
iterations of large vectors.
# Thanks.
__
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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] correlation between categorical data
For measures of association between two variables with two values each,
Cramer's V and Yule's Q are useful statistics. Look into this thread, for
example: http://markmail.org/message/sjd53z2dv2pb5nd6
To get a grasp from plotting (sometimes), you may use the jitter function in
the plot...
e=rnorm(n,0,1)
y=x+e
xprob=exp(x)/(1+exp(x))
yprob=exp(y)/(1+exp(y))
xcat=rbinom(n,1,xprob)
ycat=rbinom(n,1,yprob)
plot(ycat~xcat) #totally useless
plot(jitter(ycat)~jitter(xcat)) #can be somewhat useful
table(ycat,xcat) # interesting
#A measure of correlation between nominal variables
yule.Q=function(x,y){(table(x,y)[1,1]*table(x,y)[2,2]-table(x,y)[1,2]*table(
x,y)[2,1])/(table(x,y)[1,1]*table(x,y)[2,2]+table(x,y)[1,2]*table(x,y)[2,1])
}
yule.Q(ycat,xcat)
Best,
Daniel
-
cuncta stricte discussurus
-
-Ursprüngliche Nachricht-
Von: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Im
Auftrag von Marc Schwartz
Gesendet: Saturday, June 20, 2009 7:37 PM
An: Jason Morgan
Cc: r-help
Betreff: Re: [R] correlation between categorical data
On Jun 20, 2009, at 2:05 PM, Jason Morgan wrote:
On 2009.06.19 14:04:59, Michael wrote:
Hi all,
In a data-frame, I have two columns of data that are categorical.
How do I form some sort of measure of correlation between these two
columns?
For numerical data, I just need to regress one to the other, or do
some pairs plot.
But for categorical data, how do I find and/or visualize correlation
between the two columns of data?
As Dylan mentioned, using crosstabs may be the easiest way. Also, a
simple correlation between the two variables may be informative. If
each variable is ordinal, you can use Kendall's tau-b (square table)
or tau-c (rectangular table). The former you can calculate with ?cor
(set method=kendall), the latter you may have to hack something
together yourself, there is code on the Internet to do this. If the
data are nominal, then a simple chi-squared test (large-n) or Fisher's
exact test (small-n) may be more appropriate. There are rules about
which to use when one variable is ordinal and one is nominal, but I
don't have my notes in front of me. Maybe someone else can provide
more assistance (and correct me if I'm wrong :).
I would be cautious in recommending the Fisher Exact Test based upon small
samples sizes, as the FET has been shown to be overly conservative. This
also applies to the use of the continuity correction for the chi-square test
(which replicates the behavior of the FET).
For more information see:
Chi-squared and Fisher-Irwin tests of two-by-two tables with small sample
recommendations Ian Campbell Stat in Med 26:3661-3675; 2007
http://www3.interscience.wiley.com/journal/114125487/abstract
and:
How conservative is Fisher's exact test?
A quantitative evaluation of the two-sample comparative binomial trial
Gerald G. Crans, Jonathan J. Shuster Stat Med. 2008 Aug 15;27(18):3598-611.
http://www3.interscience.wiley.com/journal/117929459/abstract
Frank also has some comments here (bottom of the page):
http://biostat.mc.vanderbilt.edu/wiki/Main/DataAnalysisDisc#Some_Important_P
oints_about_Cont
More generally, Agresti's Categorical Data Analysis is typically the first
reference in this domain to reach for. There is also a document written by
Laura Thompson which provides for a nice R companion to Agresti. It is
available from:
https://home.comcast.net/~lthompson221/Splusdiscrete2.pdf
HTH,
Marc Schwartz
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[R] Roxygen to ignore a block of code?
Any way to tell Roxygen to ignore a block of code? It is generating an unwanted .Rd file. I've been searching for hours for an example, scouring documentation, but no luck... Thanks. - Ken -- View this message in context: http://www.nabble.com/Roxygen-to-ignore-a-block-of-code--tp24133293p24133293.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Roxygen vs Sweave for S4 documentation
Hi Ken, I have been using R for a while. Recently, I have begun converting my package into S4 classes. I was previously using Rdoc for documentation. Now, I am looking to use the best tool for S4 documentation. It seems that the best choices for me are Roxygen and Sweave (I am fine with tex). Are there any users of Roxygen or Sweave who can comment on the strengths or weaknesses of one or othe other? Thanks in advance. For the moment proper documentation of S4 classes (with a @slot tag e.g.) is not implemented yet, but my secret hope is that this will be implemented before Peter and Manuel (in cc) will present Roxygen at DSC2009. Maybe they have further comments ? Kind regards, Tobias __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Saving output in an iterated function
Try Reduce:
f - function(d, incr = 1) with(d,
data.frame(eh = ce, be, ce = ce + be, period = period + incr))
d - data.frame(ce = ones, be = twos, period = 0)
Reduce(f, init = d, x = rep(1, 4))
Reduce(f, init = d, x = rep(1, 4), accumulate = TRUE)
On Sun, Jun 21, 2009 at 9:06 AM, Economics Guyeconomics@gmail.com wrote:
# I have a function that takes a few vectors manipulates them and then
outputs a matrix of results:
funct1 - function(eh,be){
ce - eh+be
data.frame(eh,be,ce)
}
ones - c(1,1,1)
twos - c(2,2,2)
funct1(ones,twos)
# I would like to iterate it and save the results from each iteration.
I could of course write a loop but I would like to do this is the most
efficient way possible. The best I have come up with is this:
functM - function(eh,be,period,endPeriod){
period - period+1
ce - eh+be
{if (period endPeriod)
functM(ce,be,period,endPeriod)
else data.frame(eh,be,ce,period)}
}
ones - c(1,1,1)
twos - c(2,2,2)
functM(ones,twos,0,4)
# As you can see it only reports the results form the last iteration.
Here it is the 4th iteration, but if you change the last argument of
the previous run of functM, you can see that it will always report the
final matrix. How can I have it save/store/write the results of each
iteration. I do not care if it stacks it all into the same matrix or
if I have to write.csv each time. I just want to do it in the most
efficient way possible (the actual program will run for many many
iterations of large vectors.
# Thanks.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] Alternate ways of finding number of occurrence of an element in a vector.
Answering my own question: if I explicitly garbage collecte before the benchmark then 'index' always wins, which probably also answers the original question. v-rep(1:1000,1:1000); x-5; gc(); benchmark(replications=200, columns=c(test,elapsed), order=elapsed, which=length(which(x==v)), index=length(v[v==x]), sum=sum(v==x)) Allan On 19/06/09 16:51, Allan Engelhardt wrote: When trying out a couple of different approaches to this problem I get rather different answers between runs. Anybody know why? library(rbenchmark) v-rep(1:1000,1:1000); x-5; benchmark(replications=200, columns=c(test,elapsed), order=elapsed, which=length(which(x==v)), index=length(v[v==x]), sum=sum(v==x)) test elapsed 3 sum 2.513 2 index 5.512 1 which 6.712 v-rep(1:1000,1:1000); x-5; benchmark(replications=200, columns=c(test,elapsed), order=elapsed, which=length(which(x==v)), index=length(v[v==x]), sum=sum(v==x)) test elapsed 3 sum 2.502 2 index 3.779 1 which 6.650 v-rep(1:1000,1:1000); x-5; benchmark(replications=200, columns=c(test,elapsed), order=elapsed, which=length(which(x==v)), index=length(v[v==x]), sum=sum(v==x)) test elapsed 2 index 3.796 3 sum 5.808 1 which 6.633 This pattern appears to repeat (so on the next two runs sum will win followed by index followed by sum twice followed by index ...) Allan. On 19/06/09 14:55, Praveen Surendran wrote: Hi, I have a vector v and would like to find the number of occurrence of element x in the same. Is there a way other than, sum(as.integer(v==x)) or length(which(x==v)) to do the this. I have a huge file to process and do this. Both the above described methods are pretty slow while dealing with a large vector. Please have your comments. Praveen Surendran. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Roxygen vs Sweave for S4 documentation
I have been using R for a while. Recently, I have begun converting my package into S4 classes. I was previously using Rdoc for documentation. Now, I am looking to use the best tool for S4 documentation. It seems that the best choices for me are Roxygen and Sweave (I am fine with tex). Are there any users of Roxygen or Sweave who can comment on the strengths or weaknesses of one or othe other? Thanks in advance. Sweave isn't used for writing Rdoc files. Hadley -- http://had.co.nz/ __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Alternate ways of finding number of occurrence of an element in a vector.
If one puts the gc() call prior to the expressions themselves, one
gets consistently ... different results:
library(rbenchmark)
v-rep(1:500,1:500); x-5; benchmark(
which= c(gc(),length(which(x==v))), index= c(gc(),
length(v[v==x])), sum= c(gc(), sum(v==x)),
replications=200, columns=c(test,elapsed), order=elapsed )
test elapsed
3 sum 3.299
2 index 3.536
1 which 4.172
Since the gc call takes up mor than half the time, the differences may
be more dramatic
v-rep(1:500,1:500); x-5; benchmark(
+ which= c(gc()), index= c(gc()), sum= c(gc()),
+ replications=200, columns=c(test,elapsed), order=elapsed )
test elapsed
2 index 2.621
3 sum 2.621
1 which 2.631
within( benchmark(
+ which= c(gc(),length(which(x==v))), index= c(gc(),
length(v[v==x])), sum= c(gc(), sum(v==x)),
+ replications=200, columns=c(test,elapsed),
order=elapsed ), {corrected = elapsed-2.62})
test elapsed corrected
3 sum 3.304 0.684
2 index 3.543 0.923
1 which 4.180 1.560
So the answer may not be so simple.
Allan Engelhardt wrote:
Answering my own question: if I explicitly garbage collecte before the
benchmark then 'index' always wins, which probably also answers the
original question.
v-rep(1:1000,1:1000); x-5; gc(); benchmark(replications=200,
columns=c(test,elapsed), order=elapsed,
which=length(which(x==v)),
index=length(v[v==x]), sum=sum(v==x))
On 19/06/09 16:51, Allan Engelhardt wrote:
When trying out a couple of different approaches to this problem I
get
rather different answers between runs. Anybody know why?
library(rbenchmark)
v-rep(1:1000,1:1000); x-5; benchmark(replications=200,
columns=c(test,elapsed), order=elapsed,
which=length(which(x==v)), index=length(v[v==x]), sum=sum(v==x))
test elapsed
3 sum 2.513
2 index 5.512
1 which 6.712
v-rep(1:1000,1:1000); x-5; benchmark(replications=200,
columns=c(test,elapsed), order=elapsed,
which=length(which(x==v)), index=length(v[v==x]), sum=sum(v==x))
test elapsed
3 sum 2.502
2 index 3.779
1 which 6.650
v-rep(1:1000,1:1000); x-5; benchmark(replications=200,
columns=c(test,elapsed), order=elapsed,
which=length(which(x==v)), index=length(v[v==x]), sum=sum(v==x))
test elapsed
2 index 3.796
3 sum 5.808
1 which 6.633
This pattern appears to repeat (so on the next two runs sum will
win
followed by index followed by sum twice followed by index ...)
On 19/06/09 14:55, Praveen Surendran wrote:
Hi,
I have a vector v and would like to find the number of
occurrence of
element x in the same.
Is there a way other than,
sum(as.integer(v==x)) or length(which(x==v))
to do the this.
I have a huge file to process and do this. Both the above described
methods
are pretty slow while dealing with a large vector.
Please have your comments.
Praveen Surendran.
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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Re: [R] error ellipse
On 2009.06.20 16:04:21, Alexandru T Codilean wrote: Dear All, I have a data set with the following structure: [A], [a], [B], [b] where [A] and [B] are measurements and [a] and [b] are the associated uncertainties. I produce [B]/[A] vs. [A] plots in R and would like to show uncertainties as error ellipses (rather than error bars). Would this be relatively easy to do in R? I would appreciate any help on this Thanks a lot Tibi The car package has an Ellipses function that draws elliptical confidence intervals for estimated model parameters. It's not exactly what you want, but the code may help you create your own function. Cheers, ~Jason -- Jason W. Morgan Graduate Student Department of Political Science *The Ohio State University* 154 North Oval Mall Columbus, Ohio 43210 __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Warning messages when using rbind
Hello, I have been using a very simple rbind approach (simple enough for me to understand) to combine data files within R. It seems to work fine, but then generates warning messages for reasons that I can't begin to understand. The text below shows the issue. testread12=read.table(C:/Files/Test100.txt, head = T) testread11=read.table(C:/Files/Test101.txt, head = T) testbind1=rbind(testread12,testread11) testbind2=rbind(testread11,testread12) The testrbind1 line generates the following message: Warning message: In `[-.factor`(`*tmp*`, ri, value = c(0.00557998, -0.058016069, : invalid factor level, NAs generated However the testrbind2 line works fine. Although the data in the files is different, the format (columns, etc) should be identical. The fact that it works in one order, but not the other, makes it very difficult for me to understand what the problem is. Files attached. Any suggestions gratefully received. Thanks, Guy Green http://www.nabble.com/file/p24130996/Test101.txt Test101.txt http://www.nabble.com/file/p24130996/Test100.txt Test100.txt -- View this message in context: http://www.nabble.com/Warning-messages-when-using-rbind-tp24130996p24130996.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
