similar to: snow Error.

I'm working with snow and created a local cluster. So far, the same code has always worked (please see below). However, now I receive a message that the connection with the nodes cannot be opened. I restarted my workstation but that didn't help. Is there a known solution for this problem? Thanks a lot for any help. bram foubert library(snow) cl =

Dear R Users, I am attempting to use snow with rmpi. My configuration is: - R Version 2.7.2, rmpi - RMPI 0.5-6 - DeinoMPI 1.1.0 - Windows Xp SP2 I can sucessfully create a cluster and execute simple commands but for some reason, I cannot change the working directory in my nodes. > noclusters<-2 > cl <- makeCluster(noclusters, type = "MPI") 2 slaves are spawned

Hi, I'm trying to use expression() to write a text to a graphic in the margin. Using: mtext(expression(beta),side=1,line=2) writes a perfect beta greek character, but I need to add a subindex "max", and I'm trying: mtext(paste(expression(beta),"max"),side=1,line=2) simply writes "beta max" in the plot. Please, Could you tell me what I'm doing wrong?

Hi, Is there a way to know which library is giving a warning? Specifically, I'm getting a set of warnings: "Too many open raster files" Thanks and best wishes, -- Javier Garc?a-Pintado Institute of Earth Sciences Jaume Almera (CSIC) Lluis Sole Sabaris s/n, 08028 Barcelona Phone: +34 934095410 Fax: +34 934110012 e-mail:jgarcia at ija.csic.es

Hello, In a nutshell, I've got a data.frame like this: > assignation <- data.frame(value=c(6.5,7.5,8.5,12.0),class=c(1,3,5,2)) > assignation value class 1 6.5 1 2 7.5 3 3 8.5 5 4 12.0 2 > and a long vector of classes like this: > x <- c(1,1,2,7,6,5,4,3,2,2,2...) And would like to obtain a vector of length = length(x), with the corresponding

Hello, I've got a data.frame like this: > > assignation <- data.frame(value=c(6.5,7.5,8.5,12.0),class=c(1,3,5,2)) > > assignation > value class 1 6.5 1 2 7.5 3 3 8.5 5 4 12.0 2 > > > and a long vector of classes like this: > > x <- c(1,1,2,7,6,5,4,3,2,2,2...) > And would like to obtain a vector of length =

Hi, The following function use to work, but now it doesn't giving the error "> CallSnow(, 100) Using snow package, asking for 2 nodes 2 slaves are spawned successfully. 0 failed. Error in checkForRemoteErrors(val) : 2 nodes produced errors; first error: no applicable method for 'lapply' applied to an object of class "list" ". Where this is the

Hi all, I am trying to use snow package to do a parallel MCMC. I have read a few guides and articles, the following is that I came up with. When I run it I got the error message: Error in checkForRemoteErrors(lapply(cl, recvResult)) : 4 nodes produced errors; first error: could not find function "ui.Next" The data is a longitudinal data with few repeated readings on a number of

Hi all, Let's say I have a long data frame and a short one, both with three colums: $east, $north, $value And I need to fill in the short$value, extracting the corresponding value from long$value, for coinciding $east and $north in both tables. I know the possibility: for (i in 1:length(short$value)){ short$value[i] <- long$value[long$east==short$east & long$north==short$north] } How

Hello, A brief question that I am not able to resolve by my own, but I presume it's easy for you: I've used apply to find the values closer to 0 in each row of a matrix: closer.to.0 <- apply(abs(myarray),MARGIN=1,"min") My question is how could I use which (or another way) to obtain a vector that indicates which columns contains these "closer to 0" values? (I

Greetings, I am having an interesting problem and I wonder if anyone else has seen this behavior. I am running R 2.11.1 with SNOW 0.3-3 on a Dell cluster running CentOS 5.5. I create my cluster using: cluster<- makeCluster(nodes,type="SOCK",port=10191) # nodes is a vector of compute nodes I then wrap a loop around clusterApplyLB to evaluate my function multiple times, with

Hi, The argument xaxt="n" for removing the x axis from a image plot does not work for me. I'm really using a function called plot.grassmeta() in library GRASS that is a wrapper for image(), but it seems to me that the problem is not in plot.grassmeta() but in image(). If I'm right could you tell me if there is a way to remove one axis from a call to image()? Thanks and wishes,

Hello, I'm using the gstat package within R for an automated procedure that uses ordinary kriging. I can see that there is a logical ("singular") atrtibute of some adjusted model semivariograms: .- attr(*, "singular")= logi TRUE I cannot find documentation about the exact meaning and the implications of this attribute, and I dont know anything about the inner calculations

Hi all, I´m having a strange problem in my rails app hosted on Tomcat: The ''div'' element which stores the validation errors of a model doesn´t seem to be ''refreshed'' after each request,so I end up with the following problem: In the first request:''5 problems ocurred'' In the second request:''10 problems ocurred'' and so on...

Buenas Tengo que analizar unos datos, donde tengo unas piezas fabricadas y el n?mero de ciclos qie aguantan hasta q se parten. Algunas piezas son de un fabricante, otras de otro,.. En cada ciclo a algunas piezas se le somete a algun tipo de tratamiento termico, a otras a otro, algunas se pintan, otras no... Por ejemplo, para una pieza tengo los siguientes datos: Ciclo. Tratamiento. Pintado.

Here is the code, assuming 8 cores in the cpu. library('modeest') library('snow') cl = makeCluster(rep('localhost', 8), 'SOCK') x = vector(length=50) x = sapply(x, function(i) i=sample(c(1,0), 1)) pastK = function(n, x, k) { if (n>k) { return(x[(n-k):(n-1)]) } else {return(NA)} } predR = function(x, k) { pastList = lapply(1:length(x), function(n)

Hi R-Core, i am using nnet and DEoptim, Xcc=matrix(rnorm(100,0.5,0.08),50,2) Ycr=matrix(rnorm(50,0.2,0.05),50,1) pred_regm1 <- function(A) { A1=A[1] A2=A[2] A3=A[3] regm1 <- nnet(Xcc,Ycr,entropy=T,size=A1,decay=A2,maxit=2000,trace=F,Hess=T,rang=A3,skip=T) dif=sum((predict(regm1,Xcc)-Ycr)^2) return(dif) } somar=DEoptim(pred_regm1,c(1,0.00001,0.01), c(25,0.999,0.95),

Hello I would like to use SNOW to parallelise some computations to be made on columns of a data frame, using different parameter values for each SNOW "worker". I gather(?) clusterMap() is the appropriate SNOW function to do something like this. I suspect the problem lies in the fact that I am only supplying one data frame argument for the flow.dat function argument yet the a, b, and x

Hola, Estoy tratando de sobreponer un mapa sobre otro, uno que sirva de ?background? y otro con datos. Mi primer intento lo hice usando el paquete PBSmapping. Aquí lo que hice: library(PBSmapping) estados <- importShapefile(?Entidades_2013.shp") #Aquí cargamos las entidades federativas (32 entidades) zonas <- importShapefile(?zm.shp?) #Aquí cargamos las zonas metropolitanas del país

Dear All, I have a question of how to export S4 class specification to clusters/workers in parallel computing. The package I used is snowfall. The problem is reproducible as follows. Any hint is greatly appreciated. Edwin Sun === begin =========== library(snowfall) sfInit(parallel = TRUE, cpus = 2) setClass("catt", representation(aa = "numeric")) setClass("dogg",