similar to: how to append new data to saved data on disk efficiently

Hi, Is there a way to get the enclosing function name within a function? For example, I would like to have a function getEnclosingFunctionName(). It works like below f = function(){ print(getEnclosingFunctionName()) } f() # will print "f" Thanks Jeff

Hi, I would like to extract the last row of each group in a data frame. The data frame is as follows Name Value A 1 A 2 A 3 B 4 B 8 C 2 D 3 I would like to get a data frame as Name Value A 3 B 8 C 2 D 3 Thank you for your suggestions in advance Jeff

Hi, I have a a vector and a data frame with two columns vec = c("C", "A", "B") dataDF = data.frame(A1 = c("B", "A", "C"), A2 = c(1,2,3)) I would like to sort the data frame by column A1 such that the order of elements in A1 is as the same as in vec. After the ordering, the data frame would be A1 A2 C

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process1(X) ... process2(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types. I would like to pass g1, g2, g3 and their arguments to f and g1,

Hi, I wonder how to pass several functions and their arguments as arguments to a function. For example, the main function is f = function(X ) { process(X) ... process(X) } I have a few functions that operate on X, e.g. g1(X, par1), g2(X, par2), g3(X, par3). par1, par2 and par3 are parameters and of different types.

Hi, I wonder how to have R automatically print stack trace produced by traceback upon errors during interactive uses. I tried the suggestions on http://old.nabble.com/Automatically-execute-traceback-when-execution-of-script-causes-error--td22368483.html#a22368775 and used options(error = recover) options(showErrorCalls = T) It just produces an extra message like "recover called

Hi, I have two questions on using the ff package and wonder if anyone who used ff can share some thoughts. I need to save a matrix as a memory-mapped file and load it back later. To save the matrix, I use mat = matrix(1:20, 4, 5) matFF = ff(mat, dim=dim(mat), filename="~/a.mat", overwrite=TRUE, dimnames = dimnames(mat)) To load it back, I use matFF2 = ff(vmode = "double",

Hi, I have a data set similar to the following State Gender Quantity TX Male 1 NY Female 2 TX Male 3 NY Female 4 I need to calculate cumulative sum of the quantity by State and Gender. The expected output is State Gender Quantity CumQuantity TX Male 1 1 TX Male 3 4 NY Female 2 2 NY Female 4 6 I highly appreciate if someone can give me some hints on solving that in R. Hao -- View this

Hi, I wonder what is a better way to organize a lot of R source files. I have a lot of utility functions written and store them in several source files (e.g util1.R, util2.R,..utilN.R). I also have a master file in which the source command is used to load all the util.R files. When I need to use the utility functions in a new project, I create a new R file (e.g main.R) in which I

Hi, I would like to save a few dynamically created objects to disk. The following is the basic flow of the code segment for(i = 1:10) { m = i:5 save(m, file = ...) ## ??? } To distinguish different objects to be saved, I would like to save m as m1, m2, m3 ..., to file /home/data/m1, /home/data/m2, home/data/m3, ... I tried a couple of methods on translating between object names and

Hi, I have multiple responses y1, y2, .., yn, and would like to do linear regression for each of them with x1, x2, ..., xm. Instead of doing regression n times, it it possible to do it all at once? I tried lm(y1+y2 ~ x1 + x2 + x3) and lm added y1 y2 and then did the regression. thanks Jeff

Hi, I've been slowly transitioning to saving sets of objects for a project using save() rather than cluttering my workspace and then doing save.image() However, sometimes after I have done say: save(x,y,z, file='work.Rda') and I reload it a little later and I see that I also want to save object p. Currently I need to do: save(x,y,z,p, file='work.Rda') Is there any way

Hi, I wonder how to write a function that remembers its state across its calls. For example, I would like to compute the average of the pass three values the function has seen f(1) # NA f(2) # NA f(3) # 2 f(4) # 3 This would require f to keep track of the values it has seen. In other languages like c++ or java it is easy to do by having a member variable. I am not sure how to do similar

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

I tried to build the gold plugin and receive the errors posted below. I checked out the gold plugin using "cvs -z 9 -d :pserver:anoncvs at sourceware.org:/cvs/src co src," as documented on llvm.org. Is that version bleeding edge and perhaps not stable? The first errors have to do with the libtool version. I have libtool 2.2.6 on my system, which is what the README-maintainer-mode

I have a data frame 'tmp' and a vector 'name' containing 'd2'. I want to save 'tmp' under the name hidden in 'name', and the file must have the same name, plus the extension '.rda'. So I try > tmp x y 1 1 3 2 2 4 > name [1] "d2" > assign(name, tmp) > summary(get(name)) x y Min. :1.00 Min. :3.00 1st

I tried it using file and it seems to work for saving: > data(iris) > con <- file("clipboard","w") > save(iris,ascii=T,file=con) > close(con) > readLines("clipboard") ... lengthy output follows which seems correct ... but not for loading: > con <- file("clipboard","r") > load(con) Error in load(con) : loading from

Hello I try to fit a LDA and RDA model to the same data, which has two classes. The problem now is that the training errors of the LDA model and the training error of the RDA model with alpha=0 are not the same. In my understanding this should be the case. Am I wrong? Can someone explain what the reason for this difference could be? Here my code: LDA model: =========== % x is a dataframe tmp =

The attached patch to the qemu emulation of the pcnet hardware fixes several problems. It will now only read and write a transmit or receive descriptor once. It will correctly handle transmitting frames with more than two fragments. It will discard oversize frames instead of corrupting memory. I have tested all the changes I have made and even seen an improvement in receive performance from

I'm encountering excruciatingly slow load times for character vectors in R 2.6.0-- up to 30sec for a 15K file that contains a no-attributes character vector of length ~1e4 and object size ~0.5MB. In R 2.5.1, repeated loads of the same set of files are near-instantaneous. The problem is proving tricky to reproduce consistently from scratch, so I have attached the 3 files used in the examples