similar to: vectors of matrix as iinput to lapply

Displaying 20 results from an estimated 20000 matches similar to: "vectors of matrix as iinput to lapply"

2011 Apr 09
1
For->lapply->parallel apply
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
2011 Oct 31
2
lapply and Two TimeStamps as input
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
2011 Oct 22
1
lapply to return vector
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
2011 Apr 27
6
Assignments inside lapply
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
2011 Nov 02
3
Error: serialization is too large to store in a raw vector
Dear all, I have quite large code (with lapply and mclapply) and I am getting the following error. Error: serialization is too large to store in a raw vector Is it possible to ask from R to extend the Error messages with more details? I would like to see where this problem exists. B.R Alex [[alternative HTML version deleted]]
2012 Feb 07
1
using mclapply (multi core apply) to do matrix multiplication
Dear all, I am trying to multiply three different matrices and each matrice is of size 16384,16384 the normal %*% multiplciation operator has not finished one day now. As I am running a system with many cores (and it seems that R is using only one of those) I would like to write fast a brief function that converts the typical for loops of a matrix multiplication to a set of lapply sets (mclapply
2015 Feb 26
1
iterated lapply
> 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
2015 Feb 24
2
iterated lapply
> 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 <-
2010 Feb 28
2
lapply with data frame
I'm a bit confused on how to use lapply with a data.frame. For example. lapply(data, function(x) print(x)) WHAT exactly is passed to the function. Is it each ROW in the data frame, one by one, or each column, or the entire frame in one shot? What I want to do apply a function to each row in the data frame. Is lapply the right way. A second application is to normalize a column value by
2012 Dec 11
1
Bug in mclapply?
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
2011 Apr 11
1
Mclapply and print statement
Dear all. I am using the mclapply function to split my code to the many cores my system has. It seems that is working fine. This is the parallel version of lcapply. The only problem that I seem to have is that the printf cannot print messages. The ideal to me is to have fro my function an output of the form Shadowlist<-mclapply(1:dimz, function(i) { print(sprintf('Creating the
2018 Mar 04
0
Change Function based on ifelse() condtion
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),
2018 Mar 04
2
Change Function based on ifelse() condtion
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 =
2014 Mar 27
2
mclapply Segmentation Fault for Ubuntu
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
2012 Dec 13
1
possible bug in function 'mclapply' of package parallel
Dear parallel users and developers, I might have encountered a bug in the function 'mclapply' of package 'parallel'. I construct a matrix using the same input data and code with a single difference: Once I use mclapply and the other time lapply. Shockingly the result is NOT the same. To evaluate please unpack the attached archive and execute Rscript mclapply_test.R I put the
2018 Mar 04
3
Change Function based on ifelse() condtion
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 ==
2018 Mar 04
2
Change Function based on ifelse() condtion
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,
2018 Mar 04
2
Change Function based on ifelse() condtion
@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
2019 Apr 05
2
Deep Replicable Bug With AMD Threadripper MultiCore
The following program is whittled down from a much larger program that always works on Intel, and always works on AMD's threadripper with lapply but not mclappy. With mclapply on AMD, all processes go into "suspend" mode and the program then hangs. This bug is replicable on an AMD Ryzen Threadripper 2950X 16-Core Processor (128GB RAM), running latest ubuntu 18.04. The R version
2011 Mar 22
2
Problem with mclapply -- losing output/data
Hello, I am running large simulations, which unfortunately I can't really replicate here because the code is so extensive. I rely heavily on mclapply, but I realize that I'm losing data somewhere. There are two worrisome symptoms: 1) I am getting 'NULL' as a return value for some (but not all) elements of the output when I use mclapply, but not if I use lapply > tmp2[1:3]