search for: xgrid

The package xgrid 0.1-11 is now available on CRAN.? The package provides functions to distribute and collate results from simulation studies and other computationally expensive tasks to Apple Xgrid clusters from within R. More specifically, the routines within the package facilitate access to Apple Xgrid clusters (...

The package xgrid 0.1-11 is now available on CRAN.? The package provides functions to distribute and collate results from simulation studies and other computationally expensive tasks to Apple Xgrid clusters from within R. More specifically, the routines within the package facilitate access to Apple Xgrid clusters (...

Hi, list, Sorry if I am bothering you. I am interested in using xgrid with R for distributed computing. I am using MacOS X and my R 2.1. 1 is already installed and running. The client computers are all of the same type and the same version of R has been installed on them. We have also set up xgrid on my system and client computers as well. I am wondering if any one...

Hello, I have some code to run on an XGrid cluster. Currently the code is written as a single, large job... this is no good for trying to run in parallel. To break it up I have basically taken out the highest level for-loop and am planning on batch-running many jobs, each one representing an instance of the removed loop. However, when it...

...~ ., data = trainset, type = "C-classification", kernel = "linear", scale = FALSE) # generate contour xmat = make.grid(matrix(c(testset$x, testset$y), ncol = 2, byrow=FALSE)) xgrid = as.data.frame(xmat) names(xgrid) = c("x", "y") z = predict(svm_model, xgrid) xyz_dat = as.data.frame(cbind(xgrid, z)) plot_list[[i]] = contourplot(z ~ y+x, data=xyz_dat, pretty = TRUE, xlim=c(-1,50), ylim=c(-0.001, 0.05),...

Hi, I have been trying to run R programs on the XGrid but without any sucess...it would be great help if somebody could give me an indication/steps as to how to get this running...am using a Mac OSX Leopard and the xgrid is on a tiger cluster... thanks very much in advance! [[alternative HTML version deleted]]

Anyone using or has access to ParallelR? I was looking at the page and found nothing really useful! http://www.revolution-computing.com/sitegenius/topic.php?id=195 I want to see if I can run R on a cluster of workstation, and use batch systems like Grid Engine or Xgrid: http://gridengine.sunsource.net/ http://ww.apple.com/acg/xgrid/ --Chi

...nset, > type = "C-classification", > kernel = "linear", > scale = FALSE) > # generate contour > xmat = make.grid(matrix(c(testset$x, testset$y), > ncol = 2, byrow=FALSE)) > xgrid = as.data.frame(xmat) > names(xgrid) = c("x", "y") > z = predict(svm_model, xgrid) > xyz_dat = as.data.frame(cbind(xgrid, z)) > plot_list[[i]] = contourplot(z ~ y+x, data=xyz_dat, pretty = TRUE, > xlim=c(-1,50), ylim=c(-0.001...

...ssistance in fixing the problem. Below is my function; bcidata <- read.csv("~/Desktop/Files_for_Package/data.csv"); bcidata Modelsfunc<- function(bcidata){ occupancymean.data.frame <- NULL for (k in seq(2.5,250,by=2.5)){ i <- 1000/k j <- 500/k bcidata$Xgrid <- cut(bcidata$PX, breaks = i, include.lowest = T) bcidata$Ygrid <- cut(bcidata$PY, breaks = j, include.lowest = T) bcidata$IDgrid <- with(bcidata, interaction(Xgrid,Ygrid)) bcidata$IDNgrid <- factor(bcidata$IDgrid) levels(bcidata$IDgrid) <- seq_along(levels(bcida...

...want is to find the root of the above-mentioned function, for arbitrary values of x, a, and lambda, and just specifying one value for u as a starting guess. Could anyone please give me a suggestion of how to do that? Thanks in advance. In MATLAB I do the following: function u=tukeysolve(a,lambda,xgrid) u=zeros(length(xgrid),1); old=0.001; % just a guess for i=1:length(xgrid) x=xgrid(i); u(i) = fsolve(@tuki,old,optimset('Display','Off','tolf',5e-8),x,a,lambda); old=u(i); % use previous value as new start value end function f=tuki(u,x,a,lambda) f = x - (a * u^lambda...

...the similarity to other flexible, not particularly > optimized > second-order functions. > > -thomas I'll toss in my $0.02: The following is my attempt at creating a "general outer" that works with more than two arguments. gouter <- function (x, FUN, ...) { xgrid <- as.list(do.call("expand.grid", x)) names(xgrid) <- NULL array(do.call(deparse(substitute(FUN)), c(xgrid, list(...))), dim = sapply(x, length), dimnames = x) } Here's an example: > example(gouter) gouter> gouter(list(letters[1:2], 1:3, 2:4), paste, s...

Hello, outer() is great for avoiding things like: for (val1 in val1s) { for (val2 in val2s)) { x[i,j] <- somefunction(val1, val2) } } The same can be obtained with: outer(val1s, val2s, somefunction) But what if there are three (or more) sets of values to loop over? Any way of avoiding the loops then? Thanks, -- Wolfgang Viechtbauer

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...me="plot.mefista.Rd"; charset=us-ascii Content-Description: plot.mefista.Rd Content-Disposition: attachment; filename="plot.mefista.Rd" \name{plot.mefista} \alias{plot.mefista} \title{Plot an object of class mefista.} \usage{ plot.mefista(mef,draw.style=NA,Space=mef$param$space,xgrid=mef$param$xgrid, ygrid=mef$param$ygrid,nlevels=15,ncolors=0,\dots) } %- maybe also `usage' for other objects documented here. \arguments{ \item{mef}{An object of class \code{mefista}.} \item{draw.style}{Values: 0 - linear, 1 - \code{\link{image}}, 2 - \code{\link{contour}},...

I'm running into some problems with the spacing of some faceted ggplot plots. I have a number of time series faceted to be one above another, but the scale labels of the y axes all clobber each other at the bottom/top of each. for example, try: qplot(x, y, data = data.frame(x = 1:10, y = 1:10, size = 1:10), facets = size ~ ., size = size) + scale_x_continuous(breaks = 1:10) +

...6 was pretty similar to raid 5 in the first tests, I assume it will be here too. I have the full bonnie results if anyone's interested. I also plan to come up with some basic benchmarks as we start to actually have dovecot working as we want it to. (Possibly using the macs in our labs and XGrid as a "client".. finally a use for that thing :) ) Do people have suggestions as to what to test for a primarily IMAP (+ a little POP) server? I was thinking of doing something similar to http://www.courier-mta.org/mbox-vs-maildir/ which selects a mail box, deletes and expunges a messa...

I want to create a grid of function values for use in `contour' or `persp'. The function is the log-likelihood for the gamma. The sample is stored as vector of length 20 called `Survival'. A single evaluation of the log-likelihood at, say, scale = 9 and shape = 10 would be obtained by sum(dgamma(Survival, scale = 9, shape = 10, log = TRUE)) (This may work only 0.99.0, I'm not