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...rk with multiple separate outputs which one would like to compare? (I have read something about environments, but I understood it's only for functions. I could create environments, but was not succesful in using them at all (location change or separate sandbox). Functions saveCache, loadCache, saveObject, loadObject is not really what I have in mind, too -- saveObject(list=ls(), "NewObjectFile") is not a solution either...) Thanks for any hint in advance. Cheers, Zroutik [[alternative HTML version deleted]]

If save() fails because an object is not found, it should not overwrite an existing file. > a <- 1:9 > save(a, file = "a.rda") > rm(a) > load("a.rda") > a [1] 1 2 3 4 5 6 7 8 9 > rm(a) > save(a, file = "a.rda") Error in save(a, file = "a.rda") : object 'a' not found > load("a.rda") Error in

Hi, I have been using ffsave.image() to save mixture of ff and normal objects in my workspace. e.g. ffsave.image(file = "C:\output\saveobjects", rootpath = "D:\fftempdir", safe = TRUE) It works fine but once my workspace has large (~4GB) objects, I get the error: Error in ffsave.image(file = "C:\output\savedobjects", rootpath = "D:\fftempdir", safe = TRUE) : ff image could not be renamed and is left i...

...ge, a csv file is created. But, I cannot open this file, so please ignore the following part. -------------------------------------------------------------------------------------------------- If you want to create both csv file and an object directly from the file path; > library(R.utils) > saveObject(WV6_Data_R, "~/docdis/input/ch2/WV6_Data_R_v_2016_01_01.csv") > d <- loadObject("~/docdis/input/ch2/WV6_Data_R_v_2016_01_01.csv") --------------------------------------------------------------------------------------------------- I am so sorry for my mistake. For your ref...

...e, a csv file is created. But, I cannot open this file, so please ignore the following part. ------------------------------------------------------------ -------------------------------------- If you want to create both csv file and an object directly from the file path; > library(R.utils) > saveObject(WV6_Data_R, "~/docdis/input/ch2/WV6_Data_R_v_2016_01_01.csv") > d <- loadObject("~/docdis/input/ch2/WV6_Data_R_v_2016_01_01.csv") ------------------------------------------------------------ --------------------------------------- I am so sorry for my mistake. For your re...

Hi. I have a procedure that reads a directory, loops through a set of particular .RData files, loading each one, and feeding its object(s) into a function, as follows: cvListFiles<-list.files(fnDir); for(i in grep(paste("^",pfnStub,".*\\.RData$",sep=""),cvListFiles)){ load(paste(fnDir,cvListFiles[i],sep="/")); myFunction(rliObject); rm(rliObject); };

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi I am writing simulations in R, and quite regularly, I have to save lists and objects to HDD and load it later again. So I am wondering: why is there no function to write lists (and S3, S4 objects) onto HDD WITHOUT keeping the name? What I mean is: For data.frames I can use x <- data.frame(x = runif(10)) write.table(x, "x.txt) rm(x) y

I generate and save a dataset For example exampledata<-runif(10) library("R.utils"); saveObject(exampledata, file="exampledata_9810.RData"); exampledata_9810<- loadObject("exampledata_9810.RData"); I use ex function to make alot of calculations using sink to export results (in this simply example only summary of dataset) ex<-function(data){ sink(paste("data&q...

...ma" "m4.3" [6] "post" "sigma" "WV6_Data_R" Then, > d <- WV6_Data_R # the copy of WV6_Data_R is created in the object d If you want to create both csv file and an object directly from the file path; > library(R.utils) > saveObject(WV6_Data_R, "~/docdis/input/ch2/WV6_Data_R_v_2016_01_01.csv") > d <- loadObject("~/docdis/input/ch2/WV6_Data_R_v_2016_01_01.csv") Best regards, Yohei Tanaka ========================== Yohei Tanaka Tohoku University Graduate school of Economics Doctoral student email: mari...

Dear R users, I am analysing a very large data set and I need to perform several data manipulations. The dataset is so big that the only way I can play with it without having memory problems (E.g. "cannot allocate vectors of size...") is to write a batch script to: 1. cut the data into pieces 2. save the pieces in seperate .RData files 3. Remove everything from the environment 4. load