similar to: Generalized 2D list/array/whatever?

Dear listeRs, I'm finding that apply() behaves strangely when used on a 3-d array. For example: > at <- array(1:27,dim=c(3,3,3)) > at , , 1 [,1] [,2] [,3] [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 , , 2 [,1] [,2] [,3] [1,] 10 13 16 [2,] 11 14 17 [3,] 12 15 18 , , 3 [,1] [,2] [,3] [1,] 19 22 25 [2,] 20 23 26

I have a problem where I need to have a "driver" style R program that will extend itself, given more 'source("extra.R")' style lines. IE: easy to modify by other people. The problem becomes when I would like to create an array or list of functions. Each function, possibly hundreds of them, are really created by other programs, generating an *.R file. So for

Is there a reason that array() silently ignores dimnames that are not a list but matrix() gives an error? > str(matrix(11:14, 2, 2, dimnames=c("Rows","Cols"))) Error in matrix(11:14, 2, 2, dimnames = c("Rows", "Cols")) : 'dimnames' must be a list > str(array(11:14, dim=c(2, 2), dimnames=c("Rows","Cols"))) int

Just as as.vector() takes a vector, matrix or array and returns a vector in row-major order, I'd like to write a function to take such an object and return the dimension names, pasted with some separator, as a similar vector. Here is something ugly cobbled together to demonstrate what I want: a function to work for any number of dimensions. vecnames <- function(x, sep=':') {

Hi In R 1.7 the following worked fine: > array(list(),c(2,5)) [,1] [,2] [,3] [,4] [,5] [1,] NULL NULL NULL NULL NULL [2,] NULL NULL NULL NULL NULL now in R 1.8.1 I get the error: Error in rep.int(data, t1) : invalid number of copies in "rep" In addition: Warning message: NAs introduced by coercion thanks for help, I need this possibility for storing objects (lm results) in

Hi list, In a function I am writing, I need to extract the dimension names of an array. I know this can be acheived easily using dimnames() but my problem is that I want my function to be robust when the number of dimensions varies. Consider the following case: foo <- array(data = rnorm(32), dim = c(4,4,2), dimnames=list(letters[1:4], LETTERS[1:4], letters[5:6])) # What I want is to extract

Hello, probably it is quite easy but I can get it: I have mulitple numeric vectors and a function using all of them to calculate a new value: L <- c(200,400,600) AR <- c(1.5) SO <- c(1,3,5) T <- c(30,365) fun <- function(L,AR,SO,T){ exp(L*AR+sqrt(SO)*log(T)) } How can I get an array or dataframe where all possible combinations of the factors are listed and the new value is

Here's a nasty one. The following has caused a segmentation fault and possibly also a bus error. fred <- 1:6 dim(fred) <- 6 dimnames(fred) <- list(LETTERS[1:6]) mm <- matrix(1:12, 2, 6) mm %*% fred # segmentation fault here In the case without the dimnames assignment the result is OK. Cheers, Jonathan. --please do not edit the information below-- Version: platform =

Dear list, I'm trying to add a new dim to a multidimensional array. My array looks like this a1 <- array(1:8, c(2, 2, 2)) dimnames(a1) <- list(A = c("A1", "A2"), B = c("B1", "B2"), D = c("D1", "D2")) I would like to add a new dim 'group' with the value "low".

I would like to reference array dimensions by name in an apply and a summary function. For example: apply(x, "workers", sum) Is there a better way to do this than creating a new attribute for the array and then creating new methods for apply and summary? I don't want to name the individual elements of each dimension (such as with dimnames) but rather name the dimensions. Thanks

hello R-helpers, I have an array acuracia <- array(NA, dim = c(1, 1, A, B, C)) which is first defined and in the example above with dimensions 1x1xAxBxC. My array is then filled using 3 loops (I am not well familiar yet with lapply or sapply functions so I am still a loop-user): for (i in 1:A){ for (j in 1:B){ for (k in 1:C){ acuracia[,,i,j,k] <- correlacao / (sqrt(ac)) } } } then I

Hello R-users, I'd like to load data from a CSV-file to a 3-dimensional array. However the default seems to be 2-dimensional. It would also be ok to load the data and then convert it to a 3-dimensional structure. I've been trying: dat = read.csv(filename) myArr = as.array(dat, dim = c(12,100,3)) However, I get an error message: Error in `dimnames<-.data.frame`(`*tmp*`,

[Env: R 2.11.1, Win Xp, using Eclipse/StatET] In a package I'm working on, I want to create as.matrix() and as.array() methods for a particular kind of object (log odds ratios). These are returned in a loddsratio object as the $coefficients component, a vector, but really reflect an underlying (R-1)x(C-1)xstrata array, whose attributes are contained in other components. I define coef,

Hello, I'm working with an array; I'm trying to make it so that an array of dim(42,2,2) has names whose length corresponds to that of the array, and am hoping someone with experience with this can see what I'm not doing correctly: data11 = array(0,c(41,2,2)) y = lsoda(x0,times,fhn$fn.ode,pars)#This is make.fhn() from colloc infer package# y = y[,2:3]

I posted on this topic to r-help, but never got a sufficient answer, so I'm reposting here. [Env: R 2.11.1, Win Xp, using Eclipse/StatET] In a package I'm working on, I want to create as.matrix() and as.array() methods for a particular kind of object (log odds ratios). These are returned in a loddsratio object as the $coefficients component, a vector, but really reflect an underlying

Hi everyone, I have the following problem: I want to perform a LDA with the function lda(). My data object mat.data is a matrix with dimensions > dim(mat.data) [1] 1228 44 and my grouping vector grp has length 1228: > length(grp) [1] 1228 Every time I call lda(), the following error message occurs: > lda(mat.data,grp) Error in lda.default(x, grouping, ...) : length of dimnames [2]

?? > z <- array(1:24,dim=2:4) > all.equal(f(z,3),f2(z,3)) [1] "Attributes: < Component ?dim?: Mean relative difference: 0.4444444 >" [2] "Mean relative difference: 0.6109091" In fact, > dim(f(z,3)) [1] 2 3 4 > dim(f2(z,3)) [1] 3 4 2 Have I made some sort of stupid error here? Or have I misunderstood what was wanted? Cheers, Bert Bert Gunter

Here is an alternative approach using apply(). Note that with apply() you are reversing rows or columns not indices of rows or columns so apply(junk, 2, rev) reverses the values in each column not the column indices. We actually need to use rev() on everything but the index we are interested in reversing: f2 <- function(a, wh) { dims <- seq_len(length(dim(a))) dims <-

Hello, I did send this message to r-help and got no reply, no I am resubmitting here in case this was a bit too specific for the other list. Many thanks, Iago From: Iago Mosqueira <imosqueira@suk.azti.es> To: r-help@stat.math.ethz.ch Subject: Subsetting using dimnames on S4 array-based class

I am attempting to run a Poisson EWMA model using Patrick Brandt's source code. I get the following error when I run the code: Error in dimnames(x) <- dn : length of 'dimnames' [1] not equal to array extent Dimnames(x) looks like this: [[1]] NULL [[2]] [1] "mip" "div" "nom" "unity" "mood"