similar to: lapply with data frame

> On Feb 24, 2015, at 10:50 AM, <luke-tierney at uiowa.edu> wrote: > > The documentation is not specific enough on the indented semantics in > this situation to consider this a bug. The original R-level > implementation of lapply was > > lapply <- function(X, FUN, ...) { > FUN <- match.fun(FUN) > if (!is.list(X)) > X <-

> On Feb 25, 2015, at 5:35 PM, Benjamin Tyner <btyner at gmail.com> wrote: > > Actually, it depends on the number of cores: Under current semantics, yes. Each 'stream' of function calls is lazily capturing the last value of `i` on that core. Under Luke's proposed semantics (IIUC), the result would be the same (2,4,6,8) for both parallel and serial execution. This is

Dear all, I would like to ask your help understand the subsequent steps for making my program faster. The following code: Gauslist<-array(data=NA,dim=c(dimx,dimy,dimz)) for (i in c(1:dimz)){ print(sprintf('Creating the %d map',i)); Gauslist[,,i]<-f <- GaussRF(x=x, y=y, model=model, grid=TRUE,param=c(mean,variance,nugget,scale,Whit.alpha)) } creates 100 GaussMaps (each

Thanks Simon, I will take note of the sensible default for core usage. I?m trying to achieve small scale parallelism, where tasks take 1-5 seconds and make fuller use of consumer hardware. Its not a HPC-worthy computation but even laptops these days come with 4 cores and I don?t see a reason to not make use of it. The goal for the current piece of code I?m working on is to bootstrap many

Dear all I am using lapply (actually mclapply that share the same syntax). I want to call the same function that takes as input a vector. My initial data structure is a matrix that I want to cut it to multiple vectors (one vector for every row of the matrix) and then feed that to the function by using mclapply. Could you please help me converting the matrices to nrow times vectors. I would

Dear all, I have a function that recognizes the following format for timestamps "%Y-%m-%d %H:%M:%S" my function takes two input arguments the TimeStart and TimeEnd I would like to help me create the right list with pairs of TimeStart and TimeEnd which I can feed to lapply (I am using mclapply actually).  For every lapply I want two inputs to be fed to my function. I only know how to

The attached code produces corrupted pdfs (test2.pdf, test4.pdf and test5.pdf). The resulting pdf depends on how many cores are available on the machine. I don't see why there should be any difference between the pdfs (exept for the timestamp). Doing many operations involving mclapply can increase the size of the resulting pdf by ten times! Thank you for checking this. require(multicore)

Hi, Our discussions about 64 bit R has led me to another thought. I have a nice dual core 3.0 chip inside my Linux Box (Running Fedora 11.) Is there a version of R that would take advantage of BOTH cores?? (Watching my system performance meter now is interesting, Running R will hold a single core at 100% perfectly, but the other core sites idle.) Thanks! -- Noah

Dear all I would like to ask you if an assignment can be done inside a lapply statement. For example I would like to covert a double nested for loop for (i in c(1:dimx)){ for (j in c(1:dimy)){ Powermap[i,j] <- Pr(c(i,j),c(PRX,PRY),f) } } to something like that: ij<-expand.grid(i=seq(1:dimx),j=(1:dimy)) unlist(lapply(1:nrow(ij),function(rowId) { return

From: Daniel Kaschek <daniel.kaschek at physik.uni-freiburg.de> > ... When I evaluate this list of functions by > another lapply/sapply, I get an unexpected result: all values coincide. > However, when I uncomment the print(), it works as expected. Is this a > bug or a feature? > > conditions <- 1:4 > test <- lapply(conditions, function(mycondition){ >

Dear all I have wrote the following line return(as.vector(lapply(as.data.frame(data),min,simplify=TRUE))); I want the lapply to return a vector as it returns a list with elements as shown below List of 30001 $ V1 : num -131 $ V2 : num -131 $ V3 : num -137 $ V4 : num -129 $ V5 : num -130 as you can see I have already tried the simplify=TRUE and also the as.vector() but both

Hi all, I'm trying to use the package read.table within a foreach loop. I'm grabbing 500M rows of data at a time from two different files and then doing an aggregate/tapply like function in read.table after that. I had planned on doing a foreach loop 39 times at once for the 39 files I have, but obviously that won't work until I figure out why the segfault is occurring. The

Below is my full implementation (tried to make it simple as for demonstration) Lapply_me = function(X = X, FUN = FUN, Apply_MC = FALSE, ...) { if (Apply_MC) { return(mclapply(X, FUN, ...)) } else { if (any(names(list(...)) == 'mc.cores')) { myList = list(...)[!names(list(...)) %in% 'mc.cores'] } return(lapply(X, FUN, myList)) } } Lapply_me(as.list(1:4), function(xx) { if (xx ==

Running the example in the documentation causes R to crash. dario at bioinfo:~$ R R version 3.0.3 (2014-03-06) -- "Warm Puppy" Copyright (C) 2014 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or

The reason that it works for Apply_MC=TRUE is that in that case you call mclapply(X,FUN,...) and the mclapply() function strips off the mc.cores argument from the "..." list before calling FUN, so FUN is being called with zero arguments, exactly as it is declared. A quick workaround is to change the line Lapply_me(as.list(1:4), function(xx) { to Lapply_me(as.list(1:4),

My modified function looks below : Lapply_me = function(X = X, FUN = FUN, Apply_MC = FALSE, ...) { if (Apply_MC) { return(mclapply(X, FUN, ...)) } else { if (any(names(list(...)) == 'mc.cores')) { myList = list(...)[!names(list(...)) %in% 'mc.cores'] } return(lapply(X, FUN, myList)) } } Here, I am not passing ... anymore rather passing myList On Sun, Mar 4, 2018 at 10:37 PM,

I've been using mclapply and have encountered situations where it gives errors or returns incorrect results. Here's a minimal example, which gives the error on R 2.15.2 on Mac and Linux: library(parallel) f <- function(x) NULL mclapply(1, f, mc.preschedule = FALSE, mc.cores = 1) # Error in sum(sapply(res, inherits, "try-error")) : # invalid 'type' (list) of argument

Hi R users. Apologies for the lack of concrete examples because the dataset is large, and it being so I believe is the issue. I multiple, very large datasets for which I need to generate 0/1 absence/presence columns Some include over 200M rows, with two columns that need presence/absence columns based on the strings contained within them, as an example, one set has ~29k unique values and the

Hi, As an example, I want to create below kind of custom Function which either be mclapply pr lapply Lapply_me = function(X = X, FUN = FUN, ..., Apply_MC = FALSE) { if (Apply_MC) { return(mclapply(X, FUN, ...)) } else { if (any(names(list(...)) == 'mc.cores')) { list(...) = list(...)[!names(list(...)) %in% 'mc.cores'] } return(lapply(X, FUN, ...)) } } However when Apply_MC =

@Eric - with this approach I am getting below error : Error in FUN(X[[i]], ...) : unused argument (list()) On Sun, Mar 4, 2018 at 10:18 PM, Eric Berger <ericjberger at gmail.com> wrote: > Hi Christofer, > You cannot assign to list(...). You can do the following > > myList <- list(...)[!names(list(...)) %in% 'mc.cores'] > > HTH, > Eric > > On Sun, Mar