[R] Parameters estimation for extreme value models
Thanks in advance R users I have time series data and I need to estimate the parameters involved in three different models for generalized extreme values Model 1: a, b, c are constants. Model 2: a(t)=B0+B1 t, but b, c are constants Model 3: c(t)= Exp(B0+B1 t) but a, b are constants Where a, b and c are location, scale and shape parameter respectively; t is time. Regards [[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] Parameters estimation for extreme value models
Well, then, you had better get busy and stop posting here. To learn why, read the Posting Guide. Some pointers: a) No homework help here. b) No posting in HTML. c) This list is for questions about R, not statements about your needs. --- Jeff NewmillerThe . . Go Live... DCN:jdnew...@dcn.davis.ca.usBasics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/BatteriesO.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --- Sent from my phone. Please excuse my brevity. assaedi76 assaedi76 assaed...@yahoo.com wrote: Thanks in advance R users � I have time series data and I need to estimate the parameters involved in three different models for generalized extreme values � Model 1: �a, b, c�are constants. � Model 2:�a(t)=B0+B1 t, but� b, c�are constants � Model 3:�c(t)= Exp(B0+B1 t) �but�a, b�are constants � Where a, b�and�c�are location, scale and shape parameter respectively; t is time. Regards� [[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.
Re: [R] curiosity: next-gen x86 processors and FP32?
I am no HPC expert, but I have been computing for awhile. There are already many CPU-specific optimizations built into most compilers used to compile the R source code. Anyone sincerely interested in getting work done today should get on with their work and hope that most of the power of new processors gets delivered the same way. The reason single precision is so uncommon in many computing environments is that numerical errors propagate much faster with single precision. I don't expect the typical R user to want to perform detailed uncertainty analysis every time they set up a computation to decide whether it can be computed with sufficient accuracy using SP. Most speed problems I have encountered have been related to memory (swapping, fragmentation) and algorithm inefficiency, not CPU speed. --- Jeff NewmillerThe . . Go Live... DCN:jdnew...@dcn.davis.ca.usBasics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/BatteriesO.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --- Sent from my phone. Please excuse my brevity. ivo welch ivo.we...@anderson.ucla.edu wrote: dear R experts: although my question may be better asked on the HPC R mailing list, it is really about something that average R users who don't plan to write clever HPC-optimized code would care about: is there a quantum performance leap on the horizon with CPUs? like most R average non-HPC users, I want to stick mostly to mainstream R, often with library parallel but that's it. I like R to be fast and effortless. I don't want to have to rewrite my code greatly to take advantage of my CPU. the CUDA forth-and-back on the memory which requires code rewrites makes CUDA not too useful for me. in fact, I don't even like setting up computer clusters. I run code only on my single personal machine. now, I am looking at the two upcoming processors---intel haswell (next month) and amd kaveri (end of year). does either of them have the potential to be a quantum leap for R without complex code rewrites? I presume that any quantum leaps would have to come from R using a different numerical vector engine. (I tried different compiler optimizations when compiling R (such as AVX) on the 1-year old i7-27*, but it did not really make a difference in basic R benchmarks, such as simple OLS calculations. I thought AVX would provide a faster vector engine, but something didn't really compute here. pun intended.) I would guess that haswell will be a nice small evolutionary step forward. 5-20%, perhaps. but nothing like a factor 2. [tomshardware details how intel FP32 math is 4 times as fast as double math on the i7 architecture. for most of my applications, a 4 times speedup at a sacrifice in precision would be worth it. R seems to use only doubles---even as.single is not even converting to single, much less inducing calculations to be single-precision. so I guess this is a no-go. correct?? ] kaveri's hUMA on the other hand could be a quantum leap. kaveri could have the GPU transparently offer common standard built-in vector operations that we use in R, i.e., improve the speed of many programs without the need for a rewrite, by a factor of 5? hard to believe, but it would seem that AMD actually beat Intel for R users. a big turnaround, given their recent deemphasis of FP on the CPU. (interestingly, the amd-built Xbox One and PS4 processors were also reported to have hUMA.) worth waiting for kaveri? anything I can do to drastically speed up R on intel i7 by going to FP32? regards, /iaw Ivo Welch (ivo.we...@gmail.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-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] load ff object in a different computer
Hi all, I am having trouble loading a ff object previously saved in a different computer. I have both files .ffData and .RData, and the first of them is 13Mb large from which I know the data is therein. But when I try to ffload it, checkdir error: cannot create /home/_myUser_ Permission denied unable to process home/_myUser_/Rtempdir/ff1a831d500b8d.ff. and some warnings. In the original computer, this temporary file is deleted each time I exit R, and my expectation is that data is actually stored in the .ffData and .RData that I have here. But maybe I don't realy understand the underpinnings of ff. In thois computer, my username is different, so user xyz does not exist. I tried changing the option Rtempdir but no luck. In addition, when I open the .ffData file to see what is inside, there is only a path to the ff1a831... temporary file. As information about ff package in internet is rather scarce, could anyome please help me to understand this, and possibly recover my data if it is possible? Thank you! Djordje [[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] avoiding eval parse with indexing
Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(x[1, paste(rep(, , length(dim(x)) - 1), collapse=), ]))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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] When creating a data frame with data.frame() transforms integers into factors
1. Please always cc. the list; do not reply just to me.
2. OK, I see. I ERRED. Had you cc'ed the list, someone might have
pointed this out. The correct example reproduces what you saw.
z- sample(1:10,30,rep=TRUE)
table(z)
w - data.frame(table(z))
w
z Freq
1 12
2 23
3 31
4 43
5 55
6 63
7 75
8 84
9 91
10 103
sapply(w,class)
z Freq
factor integer
This is exactly what is expected and documented. See ?table. So the
question is: What do you expect? table() produces an array whose
cross-classifying factors are the dimensions. data.frame converts this
into a data frame. Perhaps the following will help clarify:
z - data.frame(fac1= sample(LETTERS[1:3],10,rep=TRUE),
fac2 = sample(c(j,k),10,rep=TRUE))
z
fac1 fac2
1 Ak
2 Bk
3 Ck
4 Ck
5 Bk
6 Ck
7 Ck
8 Aj
9 Aj
10Cj
table(z)
fac2
fac1 j k
A 2 1
B 0 2
C 1 4
data.frame(table(z))
fac1 fac2 Freq
1Aj2
2Bj0
3Cj1
4Ak1
5Bk2
6Ck4
table(z['fac1'])
A B C
3 2 5
data.frame(table(z['fac1']))
Var1 Freq
1A3
2B2
3C5
Cheers,
Bert
On Sat, May 25, 2013 at 6:54 PM, António Camacho toin...@gmail.com wrote:
Hello Bert
Thanks for your prompt reply.
I tried your example and it worked without a problem.
But what i want is to create a data frame from the output of the function
table(), so in your example i tried sapply(data.frame(tbl),class) and the
output was z -- factor and Freq ---integer.
What is happening in the table() function that is transforming the integers
in z into values with labels ?
because when i do names(tbl) it returns each value of z as a name
I read the manual for [ but i didn't understand it completely. I have to
read the introduction to R more carefully.
I also tried using [, [[ and $ for the extraction of the values from
the 'posts' column, but the problem persisted.
Like i said, this code was taken from an example in a webpage. I contacted
the author and he confirmed me that the code worked on his machine, that was
running R 2.15.1
Maybe something changed between versions in the data.frame() ??
I really don't understant what I am doing wrong.
António
On 2013/05/26, at 01:44, Bert Gunter wrote:
Huh?
z - sample(1:10,30,rep=TRUE)
tbl - table(z)
tbl
z
1 2 3 4 5 6 7 8 9 10
4 3 2 6 3 3 2 2 2 3
data.frame(z)
z
1 5
2 2
3 4
4 1
5 6
6 4
7 10
8 4
9 3
10 8
11 10
12 4
13 3
14 9
15 2
16 2
17 6
18 1
19 4
20 7
21 9
22 10
23 7
24 5
25 5
26 6
27 8
28 1
29 1
30 4
sapply(data.frame(z),class)
z
integer
Your error: you used df['posts'] . You should have used df[,'posts'] .
The former is a data frame. The latter is a vector. Read the
Introduction to R tutorial or ?[ if you don't understand why.
-- Bert
-- Bert
On Sat, May 25, 2013 at 12:36 PM, António Camacho toin...@gmail.com
wrote:
Hello
I am novice to R and i was learning how to do a scatter plot with R using
an example from a website.
My setup is iMac with Mac OS X 10.8.3, with R 3.0.1, default install,
without additional packages loaded
I created a .csv file in vim with the following content
userID,user,posts
1,user1,581
2,user2,281
3,user3,196
4,user4,150
5,user5,282
6,user6,184
7,user7,90
8,user8,74
9,user9,45
10,user10,20
11,user11,3
12,user12,1
13,user13,345
14,user14,123
i imported the file into R using : ' df - read.csv('file.csv')
to confirm the data types i did : 'sappily(df, class) '
that returns userID -- integer ; user --- factor ; posts ---
integer
then i try to create another data frame with the number of posts and its
frequencies,
so i did: 'postFreqCount-data.frame(table(df['posts']))'
this gives me the postFreqCount data frame with two columns, one called
'Var1' that has the number of posts each user did, and another collumn
'Freq' with the frequency of each number of posts.
the problem is that if i do : 'sappily(postFreqCount['Var1'],class)' it
returns factor.
So the data.frame() function transformed a variable that was integer
(posts) to a variable (Var1) that has the same values but is factor.
I want to know how to prevent this from happening. How do i keep the
values
from being transformed from integer to factor ?
Thank you for your help
António
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and provide commented, minimal, self-contained, reproducible code.
--
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Genentech Nonclinical Biostatistics
Internal Contact Info:
Phone: 467-7374
Website:
Re: [R] What does this say? Error in rep((Intercept), nrow(a0)) : invalid 'times' argument
Mike: On Sat, May 25, 2013 at 7:24 PM, C W tmrs...@gmail.com wrote: Thomas, thanks for the cool trick. I always thought browser() was the only thing existed, apparently not. Which you would have known had you read the docs! See section 9 on Debugging in the R Language Definition Manual -- Bert Mike On Sat, May 25, 2013 at 9:09 PM, Thomas Stewart tgs.public.m...@gmail.com wrote: Mike- You can use the traceback function to see where the error is: bob - matrix(rnorm(100*180), nrow=180) yyy - rnorm(180) fit1 - cv.glmnet(bob, yyy, family=mgaussian) Error in rep((Intercept), nrow(a0)) : invalid 'times' argument traceback() 6: predict.multnet(object, newx, s, type, exact, offset, ...) 5: predict.mrelnet(glmnet.object, type = nonzero) 4: predict(glmnet.object, type = nonzero) 3: lapply(X = X, FUN = FUN, ...) 2: sapply(predict(glmnet.object, type = nonzero), length) 1: cv.glmnet(bob, yyy, family = mgaussian) So, thee error is in the predict.multnet function. If you peak at that function, you see where the function falls apart. It seems that the function wants a0 to be a matrix but in this example it is a vector. I'm not familiar enough with the package to offer advice on how to fix this. -tgs On Sat, May 25, 2013 at 4:14 PM, C W tmrs...@gmail.com wrote: Dear list, I am using glmnet. I have no idea what this error is telling me. Here's my code, bob - matrix(rnorm(100*180), nrow=180) yyy - rnorm(180) fit1 - cv.glmnet(bob, yyy, family=mgaussian) Error in rep((Intercept), nrow(a0)) : invalid 'times' argument In fact, I peeked inside cv.glmnet() using, glmnet:cv.glmnet Can't even find the error message in the code. I am clueless at the moment. Thanks in advance, Mike __ 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ 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] load ff object in a different computer
Le dimanche 26 mai 2013 à 13:53 +0200, Djordje Bajic a écrit : Hi all, I am having trouble loading a ff object previously saved in a different computer. I have both files .ffData and .RData, and the first of them is 13Mb large from which I know the data is therein. But when I try to ffload it, checkdir error: cannot create /home/_myUser_ Permission denied unable to process home/_myUser_/Rtempdir/ff1a831d500b8d.ff. and some warnings. In the original computer, this temporary file is deleted each time I exit R, and my expectation is that data is actually stored in the .ffData and .RData that I have here. But maybe I don't realy understand the underpinnings of ff. In thois computer, my username is different, so user xyz does not exist. I tried changing the option Rtempdir but no luck. In addition, when I open the .ffData file to see what is inside, there is only a path to the ff1a831... temporary file. As information about ff package in internet is rather scarce, could anyome please help me to understand this, and possibly recover my data if it is possible? Please tell us exactly how you saved that ff object. You should try to reproduce the problem with very simple data you post in your message using dput(), and provide us with all the code and the errors it triggers. Regards Thank you! Djordje [[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.
Re: [R] avoiding eval parse with indexing
On 26-05-2013, at 15:56, Martin Ivanov tra...@abv.bg wrote: Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(x[1, paste(rep(, , length(dim(x)) - 1), collapse=), ]))) Is it possible to avoid the eval parse here? How? I tried this x1 - array(runif(9),dim=c(3,3)) x2 - array(runif(8),dim=c(2,2,2)) and then x1[1] and x2[1] gave me what you wanted. I don't know if it is the coRRect way to do what you want. Berend __ 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] avoiding eval parse with indexing
Martin: Well, assuming I understand, one approach would be to first get the dim attribute of the array and then create the appropriate call using that: z - array(1:24,dim=2:4) d - dim(z) ix -lapply(d[-c(1,1)],seq_len) do.call([, c(list(z),1,1,ix)) [1] 1 7 13 19 Is that what you want? -- Bert On Sun, May 26, 2013 at 6:56 AM, Martin Ivanov tra...@abv.bg wrote: Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(x[1, paste(rep(, , length(dim(x)) - 1), collapse=), ]))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ 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] avoiding eval parse with indexing
library(abind) asub(x, 1, 1) On Sun, May 26, 2013 at 10:43 AM, Bert Gunter gunter.ber...@gene.com wrote: Martin: Well, assuming I understand, one approach would be to first get the dim attribute of the array and then create the appropriate call using that: z - array(1:24,dim=2:4) d - dim(z) ix -lapply(d[-c(1,1)],seq_len) do.call([, c(list(z),1,1,ix)) [1] 1 7 13 19 Is that what you want? -- Bert On Sun, May 26, 2013 at 6:56 AM, Martin Ivanov tra...@abv.bg wrote: Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(x[1, paste(rep(, , length(dim(x)) - 1), collapse=), ]))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ 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.
[R] Setting default graphics device options
Hi,
Is it possible to :
[1] set a default location to plot graphs in png format with specific
dimensions resolution. I want to plot to a directory which is a shared on
the network (samba share), so as to view the plots from a different machine.
[2] call dev.off() 'automagically' after a call to the plot function, by
(somehow) setting it as a default behavior in .Rprofile.site? This would be
nice to have, so as to update an image viewer running on a local machine
which keeps displaying the image(s) in the shared plot folder on the remote
machine (which runs R)
I was thinking on the lines of adding the following to .Rprofile.site :
__
prior2plot - function() {plotfile - paste('/srv/samba/share/Rplot-',
as.character(format(Sys.time(), %Y%m%d-%H%M%S)), '.png', sep='');
png(filename=plotfile, width=1280, height=800)}
setHook(before.plot.new, prior2plot())
__
However, the above does not seem to work beyond a first plot.
Best wishes,
Vishal
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Re: [R] avoiding eval parse with indexing
the code returns Error: do.call([, c(list(z),1,1,ix)) #Error in 1:24[1, 1, 1:3, 1:4] : incorrect number of dimensions May be something is missing. A.K. - Original Message - From: Bert Gunter gunter.ber...@gene.com To: Martin Ivanov tra...@abv.bg Cc: r-help@r-project.org Sent: Sunday, May 26, 2013 10:43 AM Subject: Re: [R] avoiding eval parse with indexing Martin: Well, assuming I understand, one approach would be to first get the dim attribute of the array and then create the appropriate call using that: z - array(1:24,dim=2:4) d - dim(z) ix -lapply(d[-c(1,1)],seq_len) do.call([, c(list(z),1,1,ix)) [1] 1 7 13 19 Is that what you want? -- Bert On Sun, May 26, 2013 at 6:56 AM, Martin Ivanov tra...@abv.bg wrote: Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(x[1, paste(rep(, , length(dim(x)) - 1), collapse=), ]))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ 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.
Re: [R] avoiding eval parse with indexing
Hi, You could use: library(abind) #using Berend's and Bert's example x1 - array(runif(9),dim=c(3,3)) x2 - array(runif(8),dim=c(2,2,2)) z - array(1:24,dim=2:4) #applying your code: eval(parse(text=paste0(x1[1,paste(rep(,,length(dim(x1))-1),collapse=),]))) #[1] 0.6439062 0.7139397 0.6017418 eval(parse(text=paste0(x2[1,paste(rep(,,length(dim(x2))-1),collapse=),]))) # [,1] [,2] #[1,] 0.026671344 0.2116831 #[2,] 0.003903368 0.1551140 eval(parse(text=paste0(z[1,paste(rep(,,length(dim(z))-1),collapse=),]))) # [,1] [,2] [,3] [,4] #[1,] 1 7 13 19 #[2,] 3 9 15 21 #[3,] 5 11 17 23 asub(x1,1,1,drop=TRUE) #[1] 0.6439062 0.7139397 0.6017418 asub(x2,1,1,drop=TRUE) # [,1] [,2] #[1,] 0.026671344 0.2116831 #[2,] 0.003903368 0.1551140 asub(z,1,1,drop=TRUE) # [,1] [,2] [,3] [,4] #[1,] 1 7 13 19 #[2,] 3 9 15 21 #[3,] 5 11 17 23 A.K. - Original Message - From: Martin Ivanov tra...@abv.bg To: r-help@r-project.org Cc: Sent: Sunday, May 26, 2013 9:56 AM Subject: [R] avoiding eval parse with indexing Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(x[1, paste(rep(, , length(dim(x)) - 1), collapse=), ]))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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.
[R] [Fw: Re: avoiding eval parse with indexing ]
---BeginMessage--- Dear Mr Gunter, with a slight correction: z - array(1:24,dim=2:4) d - dim(z) ix - lapply(d[-1], seq_len) do.call([, c(list(z),1,ix)) [,1] [,2] [,3] [,4] [1,]17 13 19 [2,]39 15 21 [3,]5 11 17 23 your suggestion worked and is exactly what I wanted! Thank You very much indeed! I want to get rid of all eval(parse) constructs in my code, and this was the greatest obstacle I had. Now I will be able to do this. As they say, eval parse in the code is just lack on knowledge. Best regards, Martin Оригинално писмо От: Florent D. Относно: Re: [R] avoiding eval parse with indexing До: Bert Gunter Изпратено на: Неделя, 2013, Май 26 18:07:26 EEST library(abind) asub(x, 1, 1) On Sun, May 26, 2013 at 10:43 AM, Bert Gunter wrote: Martin: Well, assuming I understand, one approach would be to first get the dim attribute of the array and then create the appropriate call using that: z - array(1:24,dim=2:4) d - dim(z) ix -lapply(d[-c(1,1)],seq_len) do.call(quot;[quot;, c(list(z),1,1,ix)) [1] 1 7 13 19 Is that what you want? -- Bert On Sun, May 26, 2013 at 6:56 AM, Martin Ivanov wrote: Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(quot;x[1quot;, paste(rep(quot;, quot;, length(dim(x)) - 1), collapse=quot;quot;), quot;]quot;))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ 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. ---End Message--- __ 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] curiosity: next-gen x86 processors and FP32?
I think this is mostly but not fully correct. most users are better off with double precision most of the time...but not all of the time if the speedup and memory savings are 4 and 2, respectively. algorithm inefficiency may well be true, too---but if I spend one week of my time (or even 3 days) to tune my program for a one time job that then saves me one week, it's a net loss. let's put a value on the time to tune algorithms...$100/hour? often, it is worth more maxing memory and CPU instead. my question is thus whether the tradeoffs are becoming even more stark. if a future vector-GPU can speed up my FP by a factor of 5, I really shouldn't spend much time tuning algorithms and write my programs in a simple straightforward way instead. YMMV. memory swapping is death, speedwise. anyone who doesn't max out RAM and uses R is myopic IMHO. unfortunately, standard i7 haswells are limited to 32GB. this makes R suitable for the analysis of data sets that are about 4-6GB in size. R is prolific in making copies of structures in memory, even if a little bit of cleverness could avoid it. x$bigstruct[bignum] - 1. R often errs on the side of non-tuning its algorithms, too. that's why data.table exists (though I don't like it for some of its semantic oddities). if it makes sense to tune algorithms, it would be as low a level as possible on behalf of software that is used by as many people as possible. then again, I am grateful that we have volunteers who develop R for free. /iaw On Sun, May 26, 2013 at 1:01 AM, Jeff Newmiller jdnew...@dcn.davis.ca.us wrote: I am no HPC expert, but I have been computing for awhile. There are already many CPU-specific optimizations built into most compilers used to compile the R source code. Anyone sincerely interested in getting work done today should get on with their work and hope that most of the power of new processors gets delivered the same way. The reason single precision is so uncommon in many computing environments is that numerical errors propagate much faster with single precision. I don't expect the typical R user to want to perform detailed uncertainty analysis every time they set up a computation to decide whether it can be computed with sufficient accuracy using SP. Most speed problems I have encountered have been related to memory (swapping, fragmentation) and algorithm inefficiency, not CPU speed. --- Jeff NewmillerThe . . Go Live... DCN:jdnew...@dcn.davis.ca.usBasics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/BatteriesO.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --- Sent from my phone. Please excuse my brevity. ivo welch ivo.we...@anderson.ucla.edu wrote: dear R experts: although my question may be better asked on the HPC R mailing list, it is really about something that average R users who don't plan to write clever HPC-optimized code would care about: is there a quantum performance leap on the horizon with CPUs? like most R average non-HPC users, I want to stick mostly to mainstream R, often with library parallel but that's it. I like R to be fast and effortless. I don't want to have to rewrite my code greatly to take advantage of my CPU. the CUDA forth-and-back on the memory which requires code rewrites makes CUDA not too useful for me. in fact, I don't even like setting up computer clusters. I run code only on my single personal machine. now, I am looking at the two upcoming processors---intel haswell (next month) and amd kaveri (end of year). does either of them have the potential to be a quantum leap for R without complex code rewrites? I presume that any quantum leaps would have to come from R using a different numerical vector engine. (I tried different compiler optimizations when compiling R (such as AVX) on the 1-year old i7-27*, but it did not really make a difference in basic R benchmarks, such as simple OLS calculations. I thought AVX would provide a faster vector engine, but something didn't really compute here. pun intended.) I would guess that haswell will be a nice small evolutionary step forward. 5-20%, perhaps. but nothing like a factor 2. [tomshardware details how intel FP32 math is 4 times as fast as double math on the i7 architecture. for most of my applications, a 4 times speedup at a sacrifice in precision would be worth it. R seems to use only doubles---even as.single is not even converting to single, much less inducing calculations to be single-precision. so I guess this is a no-go. correct?? ] kaveri's hUMA on the other hand could be a quantum leap. kaveri could have the GPU transparently offer common standard built-in vector
Re: [R] avoiding eval parse with indexing
Dear Arun, Thank You very much, your suggestion also works and seems to also be more convenient. I think though, that Mr Gunter's suggestion should be more efficient, as it uses directly the Extract operator. Thank You all very much for Your responsiveness. R does have a wonderful community! Best regards, Martin Оригинално писмо От: arun Относно: Re: [R] avoiding eval parse with indexing До: Martin Ivanov Изпратено на: Неделя, 2013, Май 26 18:48:33 EEST Hi, You could use: library(abind) #using Berend's and Bert's example x1 - array(runif(9),dim=c(3,3)) x2 - array(runif(8),dim=c(2,2,2)) z - array(1:24,dim=2:4) #applying your code: eval(parse(text=paste0(quot;x1[1quot;,paste(rep(quot;,quot;,length(dim(x1))-1),collapse=quot;quot;),quot;]quot;))) #[1] 0.6439062 0.7139397 0.6017418 eval(parse(text=paste0(quot;x2[1quot;,paste(rep(quot;,quot;,length(dim(x2))-1),collapse=quot;quot;),quot;]quot;))) # [,1] [,2] #[1,] 0.026671344 0.2116831 #[2,] 0.003903368 0.1551140 eval(parse(text=paste0(quot;z[1quot;,paste(rep(quot;,quot;,length(dim(z))-1),collapse=quot;quot;),quot;]quot;))) # [,1] [,2] [,3] [,4] #[1,] 1 7 13 19 #[2,] 3 9 15 21 #[3,] 5 11 17 23 asub(x1,1,1,drop=TRUE) #[1] 0.6439062 0.7139397 0.6017418 asub(x2,1,1,drop=TRUE) # [,1] [,2] #[1,] 0.026671344 0.2116831 #[2,] 0.003903368 0.1551140 asub(z,1,1,drop=TRUE) # [,1] [,2] [,3] [,4] #[1,] 1 7 13 19 #[2,] 3 9 15 21 #[3,] 5 11 17 23 A.K. - Original Message - From: Martin Ivanov To: r-help@r-project.org Cc: Sent: Sunday, May 26, 2013 9:56 AM Subject: [R] avoiding eval parse with indexing Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(quot;x[1quot;, paste(rep(quot;, quot;, length(dim(x)) - 1), collapse=quot;quot;), quot;]quot;))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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.
Re: [R] avoiding eval parse with indexing
Hi, Another way would be: library(arrayhelpers) slice(aperm(x1,c(2,1)),j=1) #[1] 0.6439062 0.7139397 0.6017418 slice(aperm(x2,c(2,1,3)),j=1) # [,1] [,2] #[1,] 0.026671344 0.2116831 #[2,] 0.003903368 0.1551140 slice(aperm(z,c(2,1,3)),j=1) # [,1] [,2] [,3] [,4] #[1,] 1 7 13 19 #[2,] 3 9 15 21 #[3,] 5 11 17 23 #or array(z[slice.index(z,1)==1],dim= dim(z)[2:3]) # [,1] [,2] [,3] [,4] #[1,] 1 7 13 19 #[2,] 3 9 15 21 #[3,] 5 11 17 23 array(x2[slice.index(x2,1)==1],dim= dim(x2)[2:3]) # [,1] [,2] #[1,] 0.026671344 0.2116831 #[2,] 0.003903368 0.1551140 array(x1[slice.index(x1,1)==1],dim= dim(x1)[1]) #[1] 0.6439062 0.7139397 0.6017418 A.K. - Original Message - From: arun smartpink...@yahoo.com To: Martin Ivanov tra...@abv.bg Cc: R help r-help@r-project.org; Berend Hasselman b...@xs4all.nl; Bert Gunter gunter.ber...@gene.com Sent: Sunday, May 26, 2013 11:48 AM Subject: Re: [R] avoiding eval parse with indexing Hi, You could use: library(abind) #using Berend's and Bert's example x1 - array(runif(9),dim=c(3,3)) x2 - array(runif(8),dim=c(2,2,2)) z - array(1:24,dim=2:4) #applying your code: eval(parse(text=paste0(x1[1,paste(rep(,,length(dim(x1))-1),collapse=),]))) #[1] 0.6439062 0.7139397 0.6017418 eval(parse(text=paste0(x2[1,paste(rep(,,length(dim(x2))-1),collapse=),]))) # [,1] [,2] #[1,] 0.026671344 0.2116831 #[2,] 0.003903368 0.1551140 eval(parse(text=paste0(z[1,paste(rep(,,length(dim(z))-1),collapse=),]))) # [,1] [,2] [,3] [,4] #[1,] 1 7 13 19 #[2,] 3 9 15 21 #[3,] 5 11 17 23 asub(x1,1,1,drop=TRUE) #[1] 0.6439062 0.7139397 0.6017418 asub(x2,1,1,drop=TRUE) # [,1] [,2] #[1,] 0.026671344 0.2116831 #[2,] 0.003903368 0.1551140 asub(z,1,1,drop=TRUE) # [,1] [,2] [,3] [,4] #[1,] 1 7 13 19 #[2,] 3 9 15 21 #[3,] 5 11 17 23 A.K. - Original Message - From: Martin Ivanov tra...@abv.bg To: r-help@r-project.org Cc: Sent: Sunday, May 26, 2013 9:56 AM Subject: [R] avoiding eval parse with indexing Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(x[1, paste(rep(, , length(dim(x)) - 1), collapse=), ]))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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.
Re: [R] SAPPLY function for COLUMN NULL
colnames(dd)
#[1] col1 colb
null_vector- colnames(dd)
sapply(null_vector,makeNull,dd)
# col1 colb
#[1,] NA 4
#[2,] 2 NA
#[3,] 3 2
#[4,] 4 NA
#[5,] 1 4
#[6,] NA 5
#[7,] 1 6
A.K.
I am trying to make a column value in a dataframe = NA if there is a 0
or high value in that column. I need to do this process repeatedly,
hence I have to define a function. Here is the code, that I am using and is
not working. Please advise on where I am making an error.
makeNull - function(col, data=dd) {
is.na(data[[col]]) - data[[col]] ==0
is.na(data[[col]]) - data[[col]] 99
return(data[[col]])
}
dd - data.frame(col1=c(0,2,3,4,1,0,1),colb=c(4,0,2,0,4,5,6))
null_vector=c(cola,colb)
sapply(null_vector,function(x) makeNull(x,dd))
Error in `[[-.data.frame`(`*tmp*`, col, value = logical(0)) : replacement
has 0 rows, data has 7
Thank you in advance.
-Sanjeev
__
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] Setting default graphics device options
Hi,
see the R.devices package
[http://cran.r-project.org/web/packages/R.devices/]. FYI, there is a
vignette [R.devices-overview.pdf], but for some reason it's hard find.
However it is there: help.start() - R.devices - 'User guides,
package vignettes and other documentation.' - R.devices-overview.pdf.
First, don't forget to call library(R.devices).
CREATE IMAGE FILE ATOMICALLY:
To create a PNG image file 'GaussianDensity.png' in subdirectory
figures/ (of the current working directory), do:
toPNG(GaussianDensity, aspectRatio=0.6, scale=2, {
curve(dnorm, from=-5, to=+5)
})
This will, while still using png()/dev.off() internally, (1)
automatically add filename extension, (2) set the height of the image
as 0.6 times the default width, (3) rescale height and width to be 2
times the default, and (3) make sure the PNG device is closed
afterward (no more forgetting about dev.off()).
It's also make sure not to leave incomplete image files behind in case
there's an error in your plot code. There's an option to change that
behavior too, e.g. so it instead renames the incomplete file for easy
identification.
DEFAULT OUTPUT DIRECTORY:
You can set the default output directory as:
options(devEval/args/path=/srv/samba/share/)
Then, whenever you call toPNG(), it will instead save the file to
/srv/samba/share/. If the directory is missing, it will be created
automatically.
DEFAULT FILENAME:
Currently it is not possible to set a default filename pattern.
However, you can do something like:
imgname - function() {
# NOTE: No filename extension
sprintf(Rplot-%s, format(Sys.time(), %Y%m%d-%H%M%S))
}
and then use:
toPNG(imgname(), aspectRatio=0.6, scale=2, {
curve(dnorm, from=-5, to=+5)
})
(I'll think about adding support for a default image name format).
DEFAULT DEVICE OPTIONS:
To change the default image dimensions, do:
devOptions(png, width=1280, height=800);
Importantly, in order for these devOptions() to apply, you must use
toPNG() [or devEval(png)]; they won't apply if you call png()
explicitly. To check the default options, do:
str(devOptions(png))
List of 11
$ filename : chr Rplot%03d.png
$ units : chr px
$ pointsize : num 12
$ bg: chr white
$ res : logi NA
$ family: chr sans
$ restoreConsole: logi TRUE
$ type : language c(windows, cairo, cairo-png)
$ antialias : language c(default, none, cleartype, grey, subpixel
)
$ width : num 1280
$ height: num 800
The default defaults are inferred from the default in R, so if you
don't change anything you'll get the same output as calling
png()/dev.off().
BTW, unless all of your images should have aspect ratio
800/1280=0.625, I'd recommend to use square defaults (just as the
png() device do), e.g. devOptions(png, width=1280, height=1280), and
then specify aspectRatio=0.625 in your toPNG() calls.
In addition to toPNG(), there are also toBMP(), toEPS(), toPDF(),
toSVG() and toTIFF(), with their own devOptions() settings.
Hope this is useful
Henrik
PS. From your example where all images have the same filename format
with timestamps, it almost looks like you want to do an automatic
log/archiving of image files generated. If so, I also have the
R.archive package (not yet on CRAN) in development. All you need to
do is load that package and everything else will be automatic.
Whenever R.devices creates an image file (e.g. via toPNG()), a copy of
it will be saved to ~/.Rarchive/%Y%m%d/%H%M%OS3-imgname.ext, e.g.
~/.Rarchive/2013-05-26/100330.684_GaussianDensity.png. For every
toPNG(), toPDF() etc another copy will be created with a unique
filename. That is useful when you do lots to EDA and want to go back
to that image you did a couple of hours ago. If this is what you
want, let me know and I'll show you how to get access to R.archive.
On Sun, May 26, 2013 at 8:20 AM, Vishal Belsare shoot.s...@gmail.com wrote:
Hi,
Is it possible to :
[1] set a default location to plot graphs in png format with specific
dimensions resolution. I want to plot to a directory which is a shared on
the network (samba share), so as to view the plots from a different machine.
prior2plot - function() {plotfile - paste('/srv/samba/share/Rplot-',
as.character(format(Sys.time(), %Y%m%d-%H%M%S)), '.png', sep='');
png(filename=plotfile, width=1280, height=800)}
[2] call dev.off() 'automagically' after a call to the plot function, by
(somehow) setting it as a default behavior in .Rprofile.site? This would be
nice to have, so as to update an image viewer running on a local machine
which keeps displaying the image(s) in the shared plot folder on the remote
machine (which runs R)
I was thinking on the lines of adding the following to .Rprofile.site :
__
prior2plot - function() {plotfile - paste('/srv/samba/share/Rplot-',
as.character(format(Sys.time(), %Y%m%d-%H%M%S)), '.png', sep='');
png(filename=plotfile, width=1280, height=800)}
Re: [R] avoiding eval parse with indexing: Correction
Yes, for the record, the typo in my earlier post is corrected below. (Martin's previous correction both corrected and slightly changed what I provided). -- Bert On Sun, May 26, 2013 at 7:43 AM, Bert Gunter bgun...@gene.com wrote: Martin: Well, assuming I understand, one approach would be to first get the dim attribute of the array and then create the appropriate call using that: z - array(1:24,dim=2:4) d - dim(z) ix -lapply(d[-c(1,2)],seq_len) ^ ## I typed c(1,1) previously, a mistake. do.call([, c(list(z),1,1,ix)) [1] 1 7 13 19 Is that what you want? -- Bert On Sun, May 26, 2013 at 6:56 AM, Martin Ivanov tra...@abv.bg wrote: Hello, I would like to get an advice on how the notorious eval(parse()) construct could possibly be avoided in the following example. I have an array x, which can have different number of dimensions, but I am only interested in extracting, say, the first element of the first dimension. Currently I achieve this in this way: eval(parse(text=paste0(x[1, paste(rep(, , length(dim(x)) - 1), collapse=), ]))) Is it possible to avoid the eval parse here? How? Best regards, Martin __ 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ 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] Setting default graphics device options
Sorry, forgot to add: Hi, [a somewhat different approach but] see the
R.devices package /Henrik
On Sun, May 26, 2013 at 10:14 AM, Henrik Bengtsson h...@biostat.ucsf.edu
wrote:
Hi,
see the R.devices package
[http://cran.r-project.org/web/packages/R.devices/]. FYI, there is a
vignette [R.devices-overview.pdf], but for some reason it's hard find.
However it is there: help.start() - R.devices - 'User guides,
package vignettes and other documentation.' - R.devices-overview.pdf.
First, don't forget to call library(R.devices).
CREATE IMAGE FILE ATOMICALLY:
To create a PNG image file 'GaussianDensity.png' in subdirectory
figures/ (of the current working directory), do:
toPNG(GaussianDensity, aspectRatio=0.6, scale=2, {
curve(dnorm, from=-5, to=+5)
})
This will, while still using png()/dev.off() internally, (1)
automatically add filename extension, (2) set the height of the image
as 0.6 times the default width, (3) rescale height and width to be 2
times the default, and (3) make sure the PNG device is closed
afterward (no more forgetting about dev.off()).
It's also make sure not to leave incomplete image files behind in case
there's an error in your plot code. There's an option to change that
behavior too, e.g. so it instead renames the incomplete file for easy
identification.
DEFAULT OUTPUT DIRECTORY:
You can set the default output directory as:
options(devEval/args/path=/srv/samba/share/)
Then, whenever you call toPNG(), it will instead save the file to
/srv/samba/share/. If the directory is missing, it will be created
automatically.
DEFAULT FILENAME:
Currently it is not possible to set a default filename pattern.
However, you can do something like:
imgname - function() {
# NOTE: No filename extension
sprintf(Rplot-%s, format(Sys.time(), %Y%m%d-%H%M%S))
}
and then use:
toPNG(imgname(), aspectRatio=0.6, scale=2, {
curve(dnorm, from=-5, to=+5)
})
(I'll think about adding support for a default image name format).
DEFAULT DEVICE OPTIONS:
To change the default image dimensions, do:
devOptions(png, width=1280, height=800);
Importantly, in order for these devOptions() to apply, you must use
toPNG() [or devEval(png)]; they won't apply if you call png()
explicitly. To check the default options, do:
str(devOptions(png))
List of 11
$ filename : chr Rplot%03d.png
$ units : chr px
$ pointsize : num 12
$ bg: chr white
$ res : logi NA
$ family: chr sans
$ restoreConsole: logi TRUE
$ type : language c(windows, cairo, cairo-png)
$ antialias : language c(default, none, cleartype, grey,
subpixel
)
$ width : num 1280
$ height: num 800
The default defaults are inferred from the default in R, so if you
don't change anything you'll get the same output as calling
png()/dev.off().
BTW, unless all of your images should have aspect ratio
800/1280=0.625, I'd recommend to use square defaults (just as the
png() device do), e.g. devOptions(png, width=1280, height=1280), and
then specify aspectRatio=0.625 in your toPNG() calls.
In addition to toPNG(), there are also toBMP(), toEPS(), toPDF(),
toSVG() and toTIFF(), with their own devOptions() settings.
Hope this is useful
Henrik
PS. From your example where all images have the same filename format
with timestamps, it almost looks like you want to do an automatic
log/archiving of image files generated. If so, I also have the
R.archive package (not yet on CRAN) in development. All you need to
do is load that package and everything else will be automatic.
Whenever R.devices creates an image file (e.g. via toPNG()), a copy of
it will be saved to ~/.Rarchive/%Y%m%d/%H%M%OS3-imgname.ext, e.g.
~/.Rarchive/2013-05-26/100330.684_GaussianDensity.png. For every
toPNG(), toPDF() etc another copy will be created with a unique
filename. That is useful when you do lots to EDA and want to go back
to that image you did a couple of hours ago. If this is what you
want, let me know and I'll show you how to get access to R.archive.
On Sun, May 26, 2013 at 8:20 AM, Vishal Belsare shoot.s...@gmail.com wrote:
Hi,
Is it possible to :
[1] set a default location to plot graphs in png format with specific
dimensions resolution. I want to plot to a directory which is a shared on
the network (samba share), so as to view the plots from a different machine.
prior2plot - function() {plotfile - paste('/srv/samba/share/Rplot-',
as.character(format(Sys.time(), %Y%m%d-%H%M%S)), '.png', sep='');
png(filename=plotfile, width=1280, height=800)}
[2] call dev.off() 'automagically' after a call to the plot function, by
(somehow) setting it as a default behavior in .Rprofile.site? This would be
nice to have, so as to update an image viewer running on a local machine
which keeps displaying the image(s) in the shared plot folder on the remote
machine (which runs R)
I was thinking on the lines of
Re: [R] When creating a data frame with data.frame() transforms integers into factors
Hello Bert.
I didn't reply to the list because i forgot. I hit reply instead of reply
all
Thanks for your example.
I understood now that i was trying to do something that didn't made sense and
that was why it failed.
I should have used an histogram do do a graph of the frequency of each number
of 'posts' instead of going the convoluted way around and trying to do a
scatterplot.
I now understand that table() transforms each value of the variable into a
factor and counts how many times it shows up. It makes sense that these
factors are then tranformed into character when in the data frame, because
they are not a quantity, but the representation of the number.
Thanks for the help. Problem solved.
António Brito Camacho
No dia 26/05/2013, às 15:00, Bert Gunter gunter.ber...@gene.com escreveu:
1. Please always cc. the list; do not reply just to me.
2. OK, I see. I ERRED. Had you cc'ed the list, someone might have
pointed this out. The correct example reproduces what you saw.
z- sample(1:10,30,rep=TRUE)
table(z)
w - data.frame(table(z))
w
z Freq
1 12
2 23
3 31
4 43
5 55
6 63
7 75
8 84
9 91
10 103
sapply(w,class)
z Freq
factor integer
This is exactly what is expected and documented. See ?table. So the
question is: What do you expect? table() produces an array whose
cross-classifying factors are the dimensions. data.frame converts this
into a data frame. Perhaps the following will help clarify:
z - data.frame(fac1= sample(LETTERS[1:3],10,rep=TRUE),
fac2 = sample(c(j,k),10,rep=TRUE))
z
fac1 fac2
1 Ak
2 Bk
3 Ck
4 Ck
5 Bk
6 Ck
7 Ck
8 Aj
9 Aj
10Cj
table(z)
fac2
fac1 j k
A 2 1
B 0 2
C 1 4
data.frame(table(z))
fac1 fac2 Freq
1Aj2
2Bj0
3Cj1
4Ak1
5Bk2
6Ck4
table(z['fac1'])
A B C
3 2 5
data.frame(table(z['fac1']))
Var1 Freq
1A3
2B2
3C5
Cheers,
Bert
On Sat, May 25, 2013 at 6:54 PM, António Camacho toin...@gmail.com wrote:
Hello Bert
Thanks for your prompt reply.
I tried your example and it worked without a problem.
But what i want is to create a data frame from the output of the function
table(), so in your example i tried sapply(data.frame(tbl),class) and the
output was z -- factor and Freq ---integer.
What is happening in the table() function that is transforming the integers
in z into values with labels ?
because when i do names(tbl) it returns each value of z as a name
I read the manual for [ but i didn't understand it completely. I have to
read the introduction to R more carefully.
I also tried using [, [[ and $ for the extraction of the values from
the 'posts' column, but the problem persisted.
Like i said, this code was taken from an example in a webpage. I contacted
the author and he confirmed me that the code worked on his machine, that was
running R 2.15.1
Maybe something changed between versions in the data.frame() ??
I really don't understant what I am doing wrong.
António
On 2013/05/26, at 01:44, Bert Gunter wrote:
Huh?
z - sample(1:10,30,rep=TRUE)
tbl - table(z)
tbl
z
1 2 3 4 5 6 7 8 9 10
4 3 2 6 3 3 2 2 2 3
data.frame(z)
z
1 5
2 2
3 4
4 1
5 6
6 4
7 10
8 4
9 3
10 8
11 10
12 4
13 3
14 9
15 2
16 2
17 6
18 1
19 4
20 7
21 9
22 10
23 7
24 5
25 5
26 6
27 8
28 1
29 1
30 4
sapply(data.frame(z),class)
z
integer
Your error: you used df['posts'] . You should have used df[,'posts'] .
The former is a data frame. The latter is a vector. Read the
Introduction to R tutorial or ?[ if you don't understand why.
-- Bert
-- Bert
On Sat, May 25, 2013 at 12:36 PM, António Camacho toin...@gmail.com
wrote:
Hello
I am novice to R and i was learning how to do a scatter plot with R using
an example from a website.
My setup is iMac with Mac OS X 10.8.3, with R 3.0.1, default install,
without additional packages loaded
I created a .csv file in vim with the following content
userID,user,posts
1,user1,581
2,user2,281
3,user3,196
4,user4,150
5,user5,282
6,user6,184
7,user7,90
8,user8,74
9,user9,45
10,user10,20
11,user11,3
12,user12,1
13,user13,345
14,user14,123
i imported the file into R using : ' df - read.csv('file.csv')
to confirm the data types i did : 'sappily(df, class) '
that returns userID -- integer ; user --- factor ; posts ---
integer
then i try to create another data frame with the number of posts and its
frequencies,
so i did: 'postFreqCount-data.frame(table(df['posts']))'
this gives me the postFreqCount data frame with two columns, one called
'Var1' that has the number of posts each user did, and another collumn
'Freq' with the frequency of each
Re: [R] Mapping GWR Results in R
Patrick Likongwe patricklikongwe at yahoo.co.uk writes: Dear Team, Help me out here. I have managed to run a Geographically Weighted Regression in R with all results coming up. The problem now comes in mapping the parameter estimates and the t values that are significant in the model. My data is like this: The data appear to have point support, so the output of gwr() will include a SpatialPointsDataFrame - if you look at summary(gwr.model0$SDF), you will see that it is a SpatialPointsDataFrame. Consequently, a plot() of the points will show coloured points. Nothing in the your work suggests that the GWR results are being calculated for polygons. Please only use GWR for exploration, never look at any inferential output - look for spatial patterning in the mapped coefficients that corresponds with identifiable missing covariates. Then include these, and use non-GWR methods. Please also use the R-sig-geo list, not this general list. [[alternative HTML version deleted]] Do not post HTML! __ 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] load ff object in a different computer
i *SOLVED* Thanks Milan, I have receivd some feedback externally to the list and managed to solve the issue. I saved the document as follows: x.Arr - ff(NA, dim=rep(ngen,3), vmode=double) ffsave (x.Arr, file=x.Arr) finalizer(x.Arr) - delete The problem was related to the rootpath argument. As the one in one computer does not exist in the other, the solution was to set it when ffloading, so: ffload(file=/path/to/saved/x.Arr, rootpath = /path/on/your/other/computer/where/to/extract/x.Arr) Cheers, Djordje 2013/5/26 Milan Bouchet-Valat nalimi...@club.fr Le dimanche 26 mai 2013 à 13:53 +0200, Djordje Bajic a écrit : Hi all, I am having trouble loading a ff object previously saved in a different computer. I have both files .ffData and .RData, and the first of them is 13Mb large from which I know the data is therein. But when I try to ffload it, checkdir error: cannot create /home/_myUser_ Permission denied unable to process home/_myUser_/Rtempdir/ff1a831d500b8d.ff. and some warnings. In the original computer, this temporary file is deleted each time I exit R, and my expectation is that data is actually stored in the .ffData and .RData that I have here. But maybe I don't realy understand the underpinnings of ff. In thois computer, my username is different, so user xyz does not exist. I tried changing the option Rtempdir but no luck. In addition, when I open the .ffData file to see what is inside, there is only a path to the ff1a831... temporary file. As information about ff package in internet is rather scarce, could anyome please help me to understand this, and possibly recover my data if it is possible? Please tell us exactly how you saved that ff object. You should try to reproduce the problem with very simple data you post in your message using dput(), and provide us with all the code and the errors it triggers. Regards Thank you! Djordje [[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. [[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] Boundaries of consecutive integers
How's this: big.gap = diff(test) 1 cbind(test[c(TRUE, big.gap)], test[c(big.gap, TRUE)]) -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Lizzy Wilbanks Sent: Tuesday, 14 May 2013 1:18p To: r-help@r-project.org Subject: [R] Boundaries of consecutive integers Hi folks, I'm trying to accomplish something that seems like it should be straightforward, but I've gotten tied in knots trying to figure it out. A toy example of my issue is below. I've played with diff and can't seem to figure out a systematic solution that will give me the two column output independent of the number of breakpoints in the vector... test-c(1:5, 22:29,33:40) example.output-matrix(c(1,5,22,29,33,40),nrow=3,ncol=2,byrow=TRUE) Any ideas? Thanks! Lizzy -- The obvious goal of any bacterium is to become bacteria. Lizzy Wilbanks Graduate Student, Eisen and Facciotti Labs UC Davis, Microbiology Graduate Group __ 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.
