similar to: proposal for

I'd like to propose adding "strict" versions of the subsetting operators "[", "[[", and "$" to the R language. These strict versions would be intended for use in programming rather than in interactive use. They do not perform any form of partial string matching or opportunistic simplification such as dimension dropping by default. They allow more

I've put this in (with some different wording). Although S blithely accepts mis-dimensioned index matrices I agree this is wrong and have made it an error. On Fri, 29 Apr 2005 tplate@acm.org wrote: > This message contains a description of what looks like a bug, examples > of the suspect behavior, a proposed change to the C code to change this > behavior, example of behavior with

There is a new version of the abind package on CRAN (abind_1.1-0). abind() is a multi-dimensional generalization of cbind() and rbind() -- it can bind multiple 2-d matrices into a 3-d array, or bind 3-d arrays together, etc. In this new version the behavior of the function abind() has been enhanced slightly (it can now accept a list as the first argument, removing the need to use do.call()

There is a new version of the abind package on CRAN (abind_1.1-0). abind() is a multi-dimensional generalization of cbind() and rbind() -- it can bind multiple 2-d matrices into a 3-d array, or bind 3-d arrays together, etc. In this new version the behavior of the function abind() has been enhanced slightly (it can now accept a list as the first argument, removing the need to use do.call()

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

Hi everyone I've been playing with do.call() but I'm having problems understanding it. I have a list of "n" elements, each one of which is "d" dimensional [actually an n-by-n-by ... by-n array]. Neither n nor d is known in advance. I want to bind the elements together in a higher-dimensional array. Toy example follows with d=n=3. f <-

Hi, R newb here. I've coded a function that inputs N dimensional array(s) [or class=numeric if it's dim=1] of coefficients and tstats, where dim(coef_matrix)=dim(tstat_matrix), it will then output a same dimension matrix of coefficients pasted to tstats in brackets pasted to significance stars. If I go straight to the code INSIDE the function, it works 100% as it's supposed to. The

Hi Is it possible to subset an n-dimensional array by a vector of n dimensions? E.g. assume I have > x <- array(1:24, dim=2:4) > x[1,1,2] [1] 7 > dims <- c(1,1,2) I would like a function that I can supply x and dims as parameters to, and have it return 7. Also, I would like to do something like: > x[1,1,] [1] 1 7 13 19 > dims2<- c(1,1,NA) And have a function of x and

Hi I have two arbitrarily dimensioned arrays, "a" and "b", with length(dim(a))==length(dim(b)). I want to form a sort of "corner-to-corner" version of abind(), or a multidimensional version of blockdiag(). In the case of matrices, the function is easy to write and if a=matrix(1,3,4) and b=matrix(2,2,2), then adiag(a,b) would return: [,1] [,2] [,3] [,4] [,5]

>>>>> Gabriel Becker >>>>> on Tue, 29 Oct 2019 12:43:15 -0700 writes: > Hi all, > So I've started working on this and I ran into something that I didn't > know, namely that for x a multi-dimensional (2+) array, head(x) and tail(x) > ignore dimension completely, treat x as an atomic vector, and return an > (unclassed)

Hello, I am encountering some problems when overloading the "[" operator for a new S4 class based on array. This is an example class definition: setClass("foo", representation("array"), prototype(array(NA, dim=c(3,3)), dimnames=list(age=1:3, year=10:12)) ) And this the corresponding setMethod with print estatements to see what is being passed:

Hi all, I'm not sure if this is a feature or a bug (and I did read the FAQ and the posting guide, but am still not sure). Some of my students have been complaining and I thought I just might ask: Let K be a vector of length k. If one types dim(K), you get NULL rather than [1] k. Is this logical? Here's the way I explain it (and maybe someone can provide a more accurate

Jean-Claude: Well, here's my "explanation". Caveat emptor! Note that: "simplify2array() is the utility called from sapply() when simplify is not false" and > sapply(a, I, simplify = "array") [,1] [,2] [1,] list,2 list,2 [2,] list,2 list,2 So it seems that simplify2array() is not intended to operate in the way that you expected, i.e. that recursive

Gudday, I've had a good look everywhere trying to figure out how to do this, but I'm afraid I can seem to find an answer anywhere - maybe its because I'm not using the right terms, or maybe its because I'm a dummy. But unfortunately, I am not completely and utterly stuck. Here's the problem: I have two large, six dimensional arrays that I would like to add together. Lets call

Hadley, On Sat, Jul 7, 2018 at 1:32 PM, Hadley Wickham <h.wickham at gmail.com> wrote: > On Sat, Jul 7, 2018 at 1:50 PM, Gabe Becker <becker.gabe at gene.com> wrote: > > Hadley, > > > >> > >> I was thinking primarily of completing the set of is.matrix() and > >> is.array(), or generally, how do you say: is `x` a 1d dimensional > >>

Dear all, I have been working on an idempotent version of apply, such that applying a function f(x) = x (ie. force) returns the same array (or a permutation of it depending on the order of the margins): a <- array(1:27, c(2,3,4)) all.equal(a, iapply(a, 1, force)) all.equal(a, iapply(a, 1:2, force)) all.equal(a, iapply(a, 1:3, force)) all.equal(aperm(a, c(2,1,3)), iapply(a, 2, force))

On 10/30/19 04:29, Martin Maechler wrote: >>>>>> Gabriel Becker >>>>>> on Tue, 29 Oct 2019 12:43:15 -0700 writes: > > > Hi all, > > So I've started working on this and I ran into something that I didn't > > know, namely that for x a multi-dimensional (2+) array, head(x) and tail(x) > > ignore dimension

Hi, I have noticed that aperm is very slow, and I wondered if there was a way of speeding it up. Let me tell you a bit about the context of my problem, because perhaps I shouldn't be using aperm at all. The context is probabilistic inference in graphical models. One of the most fundamental operations is two compute an element-wise multiplication of two arrays of different sizes, say A and B.

Thanks to all for responses/. There was a question of exactly what was wanted. It is the generalization of the obvious example I gave, >>> junk1 <- junk[, rev(seq_len(10), ] so that junk[1,1,1 ] = junk1[1,10,1] junk[1,2,1] = junk1[1,9,1] etc. The genesis of this is the program is downloading data from a variety of sources on (time, altitude, lat, lon) coordinates, but all

Hi everyone, I created a four dimensional vector (dim (128,128,1,8)). This third dimension is necessary for another function somewhere. Now I'd like to perform a t-test on every vector of length 8 in my array on the fourth dimension. I'd like to obtain a new array of three dimensions with dimensions 128x128x1 with all these test statistics. I tried this with a double loop: A <-