similar to: "select: bad file descriptor" in the multicore package

Hi, Is there a way to get the enclosing function name within a function? For example, I would like to have a function getEnclosingFunctionName(). It works like below f = function(){ print(getEnclosingFunctionName()) } f() # will print "f" Thanks Jeff

Hi, I would like to extract the last row of each group in a data frame. The data frame is as follows Name Value A 1 A 2 A 3 B 4 B 8 C 2 D 3 I would like to get a data frame as Name Value A 3 B 8 C 2 D 3 Thank you for your suggestions in advance Jeff

Hi, I have a a vector and a data frame with two columns vec = c("C", "A", "B") dataDF = data.frame(A1 = c("B", "A", "C"), A2 = c(1,2,3)) I would like to sort the data frame by column A1 such that the order of elements in A1 is as the same as in vec. After the ordering, the data frame would be A1 A2 C

My long-promised Rdsm package is now on CRAN. Some of you may recall that I made a prototype available on my own Web page last July. This is the official version, much evolved since I released the prototype. The CRAN description states: Provides a threads-like programming environment for R, usable both on a multicore machine and across a network of multiple machines. The package

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process1(X) ... process2(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types. I would like to pass g1, g2, g3 and their arguments to f and g1,

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process(X) ... process(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types.

Sir, I want to apply mclapply() function for my analysis. So, I have to install multicore package. But I can not install the package. >install.packages("multicore") It gives that package multicore is not available. Can you help me? Regards, Suman Dhara [[alternative HTML version deleted]]

Hi, I want to parallelize some computations when it's possible on multicore machines. Each computation produces a big objects that I don't want to store if not necessary: in the end only the object that best fits my data have to be returned. In non-parallel mode, a single gloabl object is updated if the current computation gets a better result than the best previously found. My plan

It is so difficult ... Which FE? It need BE support? I didn't get it. 2010/8/4 vijay kumar <vijaygbvv at gmail.com> > Yeah OpenMP support. I read that it has a front end support but not the > back end. So are there any projects or teams looking at this issue. > > On Wed, Aug 4, 2010 at 7:24 AM, Liu <proljc at gmail.com> wrote: > >> Multicore? >> You

Hi all, I am new to this LLVM. I went through the documenation of LLVM but I didn't find any support for Multicore. Is there any such possibility where multicore architecture can be exploited using LLVM. Thanks Vijay -------------- next part -------------- An HTML attachment was scrubbed... URL:

On Aug 3, 2010, at 8:48 PM, Liu wrote: > It is so difficult ... > Which FE? It need BE support? I didn't get it. > > 2010/8/4 vijay kumar <vijaygbvv at gmail.com> > Yeah OpenMP support. I read that it has a front end support but not the back end. So are there any projects or teams looking at this issue. > > On Wed, Aug 4, 2010 at 7:24 AM, Liu <proljc at

Hello All, In general when we use Rprof for performance evaluation on Multicore systems the output provides the time on the basis of the "user" time and the sampling time is equal to the the user time as reported by system.time. This does not seem right behavior when R is linked to BLAS/Lapack or other libraries which are optimized for parallel or multicore architectures as

Hello All, In general when we use Rprof for performance evaluation on Multicore systems the output provides the time on the basis of the "user" time and the sampling time is equal to the the user time as reported by system.time. This does not seem right behavior when R is linked to BLAS/Lapack or other libraries which are optimized for parallel or multicore architectures as

Is there any reason to expect a problem ? i'm running this script on the cluster down the hall: module load R/2.11.0 R library(multicore) fxx<-function(ll) runif(1) mclapply(1:10,fxx) i get: Error in fork() : Unable to fork. less /proc/cpuinfo yields: processor : 0 vendor_id : GenuineIntel cpu family : 6 model : 15 model name : Intel(R) Xeon(R) CPU

Hi, I wonder how to have R automatically print stack trace produced by traceback upon errors during interactive uses. I tried the suggestions on http://old.nabble.com/Automatically-execute-traceback-when-execution-of-script-causes-error--td22368483.html#a22368775 and used options(error = recover) options(showErrorCalls = T) It just produces an extra message like "recover called

Hi, I currently combine multiple processed data (data frame) into a list and save the list as ".rda" using the save command. When new data come, I load the rda file, process the new data into a data frame, append the data frame to the end of the list, and save the whole list to the disk. The loading and saving steps are quite time consuming. Since I don't need to change the old data

This is a 'rather than re-invent the wheel' post. Has anyone out there re-written combn so that it can be parallelized - with multicore, snow, or otherwise? I have a job that requires large numbers of combinations, and rather than get all of the index values, then crank it through mclapply, I was wondering if there was a way to just do this natively within a function. Just curious.

Multicore? You want OpenMP support? 2010/8/3 vijay kumar <vijaygbvv at gmail.com> > Hi all, > I am new to this LLVM. I went through the documenation of LLVM but > I didn't find any support for Multicore. Is there any such possibility where > multicore architecture can be exploited using LLVM. > > > > Thanks > Vijay > >

Hi, i have a function: zz<- (constrOptim(c(.5,0), fr, grr, ui=rbind(c(-1,0),c(1,-1)), ci=c(-0.9,0.1))) i can get the result by using command (for example): zz$par now if i can use multicore: zz<-parallel(constrOptim(c(.5,0), fr, grr, ui=rbind(c(-1,0),c(1,-1)), ci=c(-0.9,0.1))) result < collect(zz) i cant get my the result: result$par because multicore add process id. for example:

dear r experts---Is there a multicore equivalent of by(), just like mclapply() is the multicore equivalent of lapply()? if not, is there a fast way to convert a data.table into a list based on a column that lapply and mclapply can consume? advice appreciated...as always. regards, /iaw ---- Ivo Welch (ivo.welch at gmail.com)