similar to: mapply() gives seg fault

--KsGdsel6WgEHnImy Content-Type: text/plain; charset=iso-8859-1; format=flowed Content-Disposition: inline Content-Transfer-Encoding: 8bit Hi, people. Wandering in R archives, and seeing the message attached below, I noticed that: mapply(rep,times=1:4, MoreArgs=42) still segfaults on R 2.2.0, and thought I should be a good citizen and report it, even if I do not have an actual problem

Hello! I have noticed that mapply() drops names in R 2.3.1 as well as in r-devel. Here is a simple example: l <- list(a=1, b=2) k <- list(1) mapply(FUN="+", l, k) [1] 2 3 mapply(FUN="+", l, k, SIMPLIFY=FALSE) [[1]] [1] 2 [[2]] [1] 3 Help page does not indicate that this should happen. Argument USE.NAMES does not have any effect here as it used only in a bit special

I have a data frame whose first colum contains the names of the variables and whose second colum contains the values to assign to them: : kkk <- data.frame(vars=c("var1", "var2", "var3"), vals=c(10, 20, 30), stringsAsFactors=F) If I do : assign(kkk$vars[1], kkk$vals[1]) it works : var1 [1] 10 However, if I try with mapply

Dear expeRts, I am trying to wrap up a package "utilities" (for my internal use). After adding a function datNAtreat that uses mapply, R CMD check gives WARNINGs for "S3 generic/method consistency", "checking replacement functions" and?"checking foreign function calls", all of which are accompanied by the following error message: Error in .try_quietly

I'm trying to use Rprof() to identify bottlenecks and speed up a particullary slow section of code which reads in a portion of a tif file and compares each of the values to values of predictors used for model fitting. I've written up an example that anyone can run. Generally temp would be a section of a tif read into a data.frame and used later for other processing. The first portion

Hello, I would like to use mapply to avoid using a loop but for some reason, I can't seem to get it to work. I've included copies of my code below. The first set of code uses a loop (and it works fine), and the second set of code attempts to use mapply but I get a "subscript out of bounds" error. Any guidance would be greatly appreciated. Xj, Yj, and Wj are also lists, and s2,

Hello all I would like to ask your help use mapply. I have a function called findCell that takes two arguments(x,sr) where x is a vector of size two (e.g x<-c(2,3) and sr is a matrix. I would like to call many times the findCell function (thus I need mapply) for different x inputs but always for the same sr. as x is a vector of size two (two cells) I want to pass inside inside the following

Hello - I am wanting to create some Cox PH models with coxph (in package survival) using different datasets. The code below illustrates my current approach and problem with completing this. ### BEGIN R SAMPLE CODE ############################## library(survival) #Define a function to make test data makeTestDF <- function(n) { times <- sample(1:200, n, replace = TRUE) event

Dear list, this works fine: x <- split(iris, iris$Species) x1 <- lapply(x, function(L) transform(L, g = L[,1:4] * 3)) but I would like to multiply each Species with another factor: setosa by 2, versicolor by 3 and virginica by 4. I've tried mapply but without success. Any thoughts? Thanks for any idea! Patrick

List: Thank you for the replies to my post yesterday. Gabor and Phil also gave useful replies on how to improve the function by relying on mapply rather than the explicit for loop. In general, I try and use the family of apply functions rather than the looping constructs such as for, while etc as a matter of practice. However, it seems the mapply function in this case is slower (in terms of CPU

Despite the spirited arguments of various R-core folks who feel that mle() doesn't need a "data" argument, and that users would be better off learning to deal with function closures, I am *still* trying to make such things work in a reasonably smooth fashion ... Is there a standard idiom for "merging" environments? i.e., suppose a function has an environment that I want

Dear all, when I look at the internal of mapply() function, I see a line of code: answer <- .Call("do_mapply", FUN, dots, MoreArgs, environment(), PACKAGE = "base") Can somebody please tell me how to find the source code of 'do_mapply' Thanks, [[alternative HTML version deleted]]

Dear list and Hadley, The new plyr package seems to provide a clean and consistent way to apply a function on several arguments. However, I don't understand why the following example does not work like the standard mapply, library(plyr) df <- data.frame(a=1:10 , b=1:10) foo1 <- function(a, b, cc=0, d=0){ a + b + cc + d } mdply(df, foo1, cc=1) # fine mdply(df, foo1, d=1) #

Dear list, I have a matrix, spc, that should row-wise be interpolated: E.g. spc <- matrix (1:1e6, ncol = 250, nrow = 4000, byrow = TRUE) spc [1:10, 1:10] shifts <- seq_len (nrow (spc)) wl <- seq_len (ncol (spc)) interpolate <- function (spc.row, shift, wl) spline (wl + shift, spc.row, xout = wl, method = "natural")$y interpolate (spc [1,], shift = shifts [1], wl = wl)

Hello, I'm attempting to create a data frame with correlations between every pair of variables in a data frame, so that I can then sort by the value of the correlation coefficient and see which pairs of variables are most strongly correlated. The sm2vec function in the corpcor library works very nicely as shown here: library(Hmisc) library(corpcor) # Create example data x1 = runif(50) x2 =

I have a general style question about R coding. Suppose I'm writing a function (foo1) that calls other functions (foo2, foo3, ...) which have complicated argument lists (e.g. optim(), plot()), _and_ I may be calling several different functions in the body of foo1. Since foo2 and foo3 have different sets of arguments, I can't just use "..." ; I did write some code a while ago

Dear users, I have a double for loop that does exactly what I want, but is quite slow. It is not so much with this simplified example, but IRL it is slow. Can anyone help me improve it? The data and code for foo_reg() are available at the end of the email; I preferred going directly into the problematic part. Here is the code (I tried to simplify it but I cannot do it too much or else it

In an earlier post, a person wanted to divide each of the rows of rawdata by the row vector sens so he did below but didn't like it and asked if there was a better solution. rawdata <- data.frame(rbind(c(1,2,2), c(4,5,6))) sens <- c(2,4,6) temp <- t(rawdata)/sens temp <- t(temp) print(temp) Gabor sent three other solutions and I understood 2 of them but not the

Hi, Starting with ordinary vectors, so we know what to expect: > mapply(function(x, y) {x * y}, 101:106, rep(1:3, 2)) [1] 101 204 309 104 210 318 > mapply(function(x, y) {x * y}, 101:106, 1:3) [1] 101 204 309 104 210 318 Now with an S4 object: setClass("A", representation(aa="integer")) a <- new("A", aa=101:106) > length(a)

R-helpers: I'm trying to build a package, but I'm a bit new to the whole S3/S4 methods concept. I'm trying to add a new definition of the zoo function "as.yearmon", but I'm getting the following error when it gets to this point during a package install: *** R CMD INSTALL STARStools * installing to library