similar to: syntax difference clusterExport in parallel and snow

I am trying to do parallel programming and I tried this library(doSNOW) library(foreach) testfunc<-function(x){ x<-x+1 x } noc<-2 cl <- makeCluster(do.call(rbind,rep(list("localhost"),noc)), type = "SOCK") registerDoSNOW(cl) clusterExport(cl=cl,c("testfunc.r")) testl<-foreach(pp=1:2) %dopar% { testfunc(pp) } And this works but if I try to

Hi everyone, I'm aiming to run an external executable (say filetorun.EXE) in parallel. The external executable collect needed data from a file, say "input.txt" and, in turn,generates several output files, say "output.txt". I need to generate "input.txt", run the executable and keep "input.txt" and "output.txt". I'm using Windows 7, R

Dear R gurus, I have a very embarrassingly parallelizable job that I am trying to speed up with snow on our local cluster. Basically, I am doing ~50,000 t.test for a series of micro-array experiments, one gene at a time. Thus, I can easily spread the load across multiple processors and nodes. So, I have a master list object that tells me what rows to pick up for each genes to do the t.test from

Hi I try parallelising some code using the snow package and the following lines: cl <- makeSOCKcluster(8) pfunc <- function (x) (if(x <= (-th)) 1 else 0) ###correlation coefficient clusterExport(cl,c("pfunc","th")) cor.c.f <- parApply(cl,tms,c(1,2),FUN=pfunc) The parApply results in the error message: > cor.c.f <- parApply(cl,tms,c(1,2),FUN=pfunc) Error

Hello, I have been trying to write a small program to generate automatic plots. What I want is to draw boxplots for some variables in my data frame, contrasting with a variable called 'missing' that has value 1 if some variable in a concrete case has at least one missing value, in order to check if the cases that don't enter in my analysis are biased. The first attempt was to

Hi I would like to write a script that reads a list of variable names. These variable names are some of the column headers in a data.frame. Then I want do a for-loop to execute various operations on the specified variables in the data.frame, but can't figure out how to do the necessary variable substitution. In bash (or C) I would use "$var", but there seems to be no equivalent in

Hi,I use the 'lmekin' model of the 'kinship' package of R in order to estimate heritability. I want to estimate the confidence interval of the variance coefficient and so I should use a bootstrap simulation. The pedigree file has 1386 subjects so I create a kinship matrix [1386*1386].This is the code of R I use: kfit2 <- lmekin(IT~1+AGE +(1|ID), dati1,

Hello, applying a function to a list of variables I face the following problem: Let's say I want to compute tables for several variables. I could write a command for every single table, like bravo<-c(1,1,2,3,5,5,5,);charly<-c(7,7,4,4,2,1) table(bravo); table(charly) > table(bravo); table(charly) bravo 1 2 3 5 2 1 1 3 charly 1 2 4 7 1 1 2 2 The results are two tables with the

Hola: Vuelvo a la carga con algo que resolví hace años y que ahora me ha dejado de funcionar y no consigo arreglar. A ver si alguien me sugiere algún enfoque o directamente la solucion. Utilizo R en muchos procesos ETL y la cuestión es que me encuentro con que tengo que hacer inserts en un BBDD de SQL Server de varios miles (a veces millones de registros) que mientras R las realiza parece que

I am making the question clear. Please help. > Dear R experts > > I was using kinship package to fit mixed model with kinship matrix. > The package looks like lme4, but I could find a way to extract p-value > out of it. I need to extract is as I need to analyse large number of > variables (> 10000). > > Please help me: > > require(kinship) > > #Generating

Hi, I want to subset a data frame if one of the variables matches any in a list. I could of course do something like this: subset(dataset, var == 1 | var == 2 | var ==3) but that's tedious. I tried varlist = c(1,2,3,4) subset(dataset, any(var == varlist)) but it doesn't work because 'any' doesn't go row-by-row and hence always returns TRUE. Is there any simple way to do this?

Hi! I'm a recent convert from Stata, so forgive my ignorance. In Stata, I can write foreach loops (example below) foreach var of varlist p1-p14 { foreach y of varlist p15-p269 { reg `var' `y' } } It's looping p1-p15, p1-p16...., p1-p269, p2-p15, p2-p16,... p2-p269,... variable pairs. How can I write something similar in R? I 'tried' understanding the

Hello, Is the first time I am using SNOW package and I am trying to tune the cost parameter for a linear SVM, where the cost (variable cost1) takes 10 values between 0.5 and 30. I have a large dataset and a pc which is not very powerful, so I need to tune the parameters using both CPUs of the pc. Somehow I cannot manage to do it. It seems that both CPUs are fitting the model for the same values

Hello and thanks in advance for your time. I've created a simulation on my cluster which uses a custom package developed by me for different functions and also the snow package. Right now I'm using LAM to communicate between nodes and am currently only testing my code on 3 nodes for simplicity, though I plan on expanding to 16 later. My problem is this error: "Error in

Friends I can't quite find a direct answer to this question from the lists, so here goes: I have several dataframes, 200+ columns 2000+ rows. I wish to script some operations to perform on some of the variables (columns) in the data frames not knowing what the column number is, hence have to refer by name. I have variable names in a text file "varlist". So, something like this:

Hi, This is my first message to this list. It would be great if people here could help me with the following problem (self-contained code example below): I have a list of matrices and would like to apply a summary function to the matrices in the list. The matrices represent social networks, therefore I need to apply some specialized summary functions provided by the ergm package. These

Hi,? I'm trying to obtain a table of coefficients and confidence intervals from a logistic regression analysis in R. My code is as follows: # read in csv file datafile<-read.csv("file.csv", row.names=1) # read in the variable list varlist<-names(datafile)[66:180] models<-lapply(varlist, function(x) {glm(substitute(outcome ~ i, list(i=as.name(x))), data=datafile, family =

Hello all I have what seems like a simple question but have not been able to find an answer on the forum. I'm trying to define a function which involves regression models and a large number of covariates. I would like the function to accept any number of covariates and, ideally, I would like to be able to enter the covariates in a group (e.g. as a list) rather than individually. Is there any

I'm parallelizing some computation on hierarchical data, and would find it natural to do something like this (where a call to parLapply is embedded in outer call to parLapply): cl <- makeCluster(rep.int('localhost', 5), type='SOCK') clusterExport(cl, 'cl') parLapply(cl, 1:5, function(i) parLapply(cl, 1:5, function(j) i * j)) Snow

Lately, I see a dependency problem with R-3.2 systems. install.packages allows dependencies, but they are not installed so the install fails. I see this a lot with students who are able to install packages like ggplot2 but then can't load it because a dependency "stringi" is missing. Those students are generally using Windows, but today I reproduced the same on RedHat Linux with