search for: sflapply

...o_calc = function(x) {print(x*x)}) my_calc <- calculator$new() wrapper <- function(x) {my_calc$do_calc(x)} # STANZA 2: use snowfall without wrapper -- WORKING #sfInit(parallel=TRUE, cpus=2, type="SOCK") #sfExport("calculator") #sfExport("my_calc") #results <- sfLapply(1:10,my_calc$do_calc) #sfStop() #print(results) # STANZA 3: use snowfall with wrapper -- NOT WORKING # (not working by itself, but does work if the previous stanza is run first!!) sfInit(parallel=TRUE, cpus=2, type="SOCK") sfExport("calculator") sfExport("my_calc") s...

Dear all, I am trying to execute the simple example in snowfall http://cran.r-project.org/web/packages/snowfall/vignettes/snowfall.pdf ... require(snow) require(snowfall) sfInit( parallel=TRUE, cpus=2 ) sfLapply( 1:10, exp ) sfStop() I have installed the snow and snowfall packages in R on a machine with windows xp, however, after running the "sfInit( parallel=TRUE, cpus=2 )" line I get an error ... Error in system("whoami", intern = TRUE, ignore.stderr = TRUE) : whoami not found Err...

Hi Greg, I don't know if this is related to your problem, but I get the same error (on both ubuntu and fedora linux, R 2.9) and just found a very curious behaviour - snowfall apply functions don't like the variable name "c". E.g.: c<-1 sfLapply(1:10, exp) issues the same error you had posted, while subsequent rm("c") sfLapply(1:10, exp) runs fine. Rainer On Wed, 31 Dec 2008, Greg Riddick wrote: > Hello All, > > I can run the "lower level" functions OK, but many of the higher level > (eg. parSAp...

...ackages (parallel, snow, snowfall,..) but could not solve my specific problem. As far as I understood, either I have to write a new function like sfRollapplyr or I have to change my code in a way that it utilizes lapply, or sapply instead of 'rollapplyr' first then use sfInit, sfExport, and sfLapply,.. for parallel computing. I could not perform either so please help me :)   ## nc<-313 rs<-500000 ema<-10 h<-4 gomin1sd<-function (x,rho) { getOutliers(as.vector(x),rho=c(1,1))$limit[1] } dim(dt_l1_inp) [1] 500000 312 dt_l1_min1<-matrix(nrow=rs, ncol=nc-1-(ema*h)) for (i in 1:rs)...

Dear all, I just wrote a script to have each of my three mcmc chins running on a different computer core to improve computation speed. To do it I use the function sfLapply from the package snowfall. Before using parallell computation, I did my diagnostic analyses just after the model updating, but now I have to save the coda before. Using the CODA package, it is possible to load the outputs in a mcmc.list to perform some diagnostics but it doesn't work with func...

...<Anonymous> function. Of course, this can in fact be any of several functions, but I am unable to see how I could use the information from Rprof.out to discern which function is taking the most time. An example line from my Rprof.out is: rbernoulli <Anonymous> runOneRound FUN lapply sfLapply doTryCatch tryCatchOne tryCatchList tryCatch try eval.with.vis eval.with.vis source In my case, the <Anonymous> functions seem to be any of several work-horse functions, that are part of a list, and different cases are dispatched to different functions. I could of course get them all out...

R-helpers: What would be the absolute fastest way to make a large "empty" file (e.g. filled with all zeroes) on disk, given a byte size and a given number number of empty values. I know I can use writeBin, but the "object" in this case may be far too large to store in main memory. I'm asking because I'm going to use this file in conjunction with mmap to do parallel

I have data that looks like this: > df1 group id 1 red A 2 red B 3 red C 4 blue D 5 blue E 6 blue F I want a list of the groups containing vectors with the ids. I am avoiding subset(), as it is only recommended for interactive use. Here's what I have so far: df1 <- data.frame(group=c("red", "red", "red", "blue",