similar to: Difference across the Nth dimension of an array

aperm() was designed for multidimensional arrays, but is also useful for table objects, particularly with the lattice, vcd and vcdExtra packages. But aperm() was designed and implemented before other related object classes were conceived, and I propose a small tune-up to make it more generally useful. The problem is that aperm() always returns an object of class 'array', which

I'm attempting to sort a 3 dimensional array that looks like this > x , , 1 [,1] [,2] [1,] 9 9 [2,] 7 9 , , 2 [,1] [,2] [1,] 6 5 [2,] 4 6 , , 3 [,1] [,2] [1,] 2 1 [2,] 3 2 Such that it ends up like this .... > y , , 1 [,1] [,2] [1,] 2 1 [2,] 3 2 , , 2 [,1] [,2] [1,] 6 5 [2,] 4 6 , , 3 [,1] [,2]

Hello, I'm trying to switch from Matlab to R-project, and having some difficulties. I make a use of multidimensional matrices. For example, I need to extract mean from one of the dimensions: % we have matrix data of size: 130 x 11 x 350 x 2 data = data - repmat(mean(data,3),[130 1 1 1]); In R project I managed to do that in a very pervarsive way: # mean(data,3) in R base <-

Hi: How can I extract the dimension-names of a pre-defined element in a multidimensional array in R ? A toy example is provided below: I have a 4-dimensional array with each dimension having certain length. In the below example, "mydatastructure" explains the structure of my data. mydatastructure = array(0, dim=c(length(b),length(z),length(x),length(d)), dimnames=list(b,z,x,d)) where,

Hi, xtabs() creates a table of counts. I want a table of proportions -- that is, I want to divide every vector (along a particular dimension) by its sum. The tiny example below does that. The call to xtabs() creates a matrix "A" with dimensions ("x1","x2","y"). I transform "A" using aperm() and aaply() to get the matrix "B". The

Hello, A simple question, although I can't find an answer via my google/forum search: I have a 4-dimensional array; call it A[1:M,1:N,1:P,1:Q]. I have a vector x that is N by 1. I would like to "quickly" add x to the 2nd dimension of A; in other words, I want a quicker way of doing the following: for (m in 1:M) { for (p in 1:P) { for (q in 1:Q) { A[m,,p,q] =

So I'm working on a custom front end to R, in one mode of the front end I dynamically load libR.so into a child worker thread. I'm very careful to make sure it is loaded by a single thread and loaded only once, but since it is a child thread it violates assumptions made by the stack size checking inside of R and I get innumerable errors along the lines of Error: C stack usage

On the off chance that anyone is still interested, here is the corrected function using aperm(): z <- array(1:120,dim=2:5) f2 <- function(a, wh) { idx <- seq_len(length(dim(a))) dims <- setdiff(idx, wh) idx <- append(idx[-1], idx[1], wh-1) aperm(apply(a, dims, rev), idx) } all.equal(f(z, 1), f2(z, 1)) # [1] TRUE all.equal(f(z, 2), f2(z, 2)) # [1] TRUE

Thanks again. I am going to try the different versions. But I probably won't be able to get to it till next week. This is probably at the point where anything further should be sent to me privately. -Roy > On Jun 1, 2017, at 1:56 PM, David L Carlson <dcarlson at tamu.edu> wrote: > > On the off chance that anyone is still interested, here is the corrected function using

Hello all, I'm working with a matrix that will have varying dimensions. It will populate an array such that the number of matrix columns will determine the number of 3rd dimension levels of the array. Rows will be the same for both. For this example lets say the array will have 2 columns, but that's not fixed. dim(arr)<-c(dim(mat)[1],2,dim(mat)[2]) I wish to repeat each matrix

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

I think that the "dimname names" of tables and arrays could make aperm() and apply() (and probably some other functions) easier to use. (dimname names are, for example, created by table() ) The use would be something like: -- x <-table( from=sample(3,100,rep=T), to=sample(5,100,rep=T)) trans <- x / apply(x,"from",sum) y <- aperm( trans,

I am moving this to r-devel. The problem and solution below posted on r-help could have been a bit slicker if %*% worked with multidimensional arrays multiplying them so that if the first arg is a multidimensional array it is mulitplied along the last dimension (and first dimension for the second arg). Then one could have written: Tbar <- tarray %*% t(wt) / rep(wti, each = 9) which is a bit

Hi, I am looking for some generalization of colSums and rowSums for general vector valued functions, and for arrays of more than 2 dimensions. So as a concrete example, suppose I have a 3 dimensional array, given by x = array(1:100,c(3,4,5)). and I want to sum the 3rd index of x to obain a 3 by 4 matrix. Using rowSums would return a vector of length 3 because it treats the last two indices as

Hi, I have a multidimensional data-set( multiple 'x' variables with a target variable). I want to take it to a higher dimensional space so that I can apply classification technique with ease . Is there a package in R which would allow me to take these data points from lower dimensional space to higher dimensions? so that is that higher dimension I can apply classification techniques to be

It's also very common in Fortran. -David Michael Ferguson via llvm-dev <llvm-dev at lists.llvm.org> writes: >> It seems that the main advantage of your proposal is that it would >> allow for non-constant strides (i.e. variable length arrays) in >> dimensions other than the first one. Do these appear frequently >> enough in the programs

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))

I am trying to multiply a 3D array of 4x4x4 by the 4 3D arrays of a 4D array with dimensions 4x4x4x4 (the last dimension being the one that I want to split by). (4x4x4 array) > hiaAry , , a1 i1 i2 i3 i4 h1 9.5936098 6.001040 0.08772 0.3138600 h2 1.2003500 1.454570 2.79248 0.0000000 h3 0.1346500 0.201220 0.39256 0.5464000 h4 0.0109000 0.012270 0.16417 0.2766900 ,

Dear R-Helpers, I wonder whether there is a function which cuts a multiple dimensional array along a chosen dimension and then store each piece (still an array of one dimension less) into a list. For example, arr <- array(seq(1*2*3*4),dim=c(1,2,3,4)) # I made a point to set the length of the first dimension be 1to test whether I worry about drop=F option. brkArrIntoListAlong <-

OK guys another problem. I have a 3D array "x" with dim(x)=c(a,a,b^2) and I want to rearrange the elements of x to make a matrix "y" with dimensions c(a*b,a*b). Neither a nor b is known in advance. I want the "n-th" a*a submatrix of y to be x[,,n] (where 1 <= n <= b^2). Needless to say, this has gotta be vectorized! Toy example with a=2, b=3 follows: