similar to: Help with multidimensional array

I often use Lyx/Sweave and I typically write in english. Today I had to write a document in Italian and, as many of you know, many italian popular words use ?, ?, ?. ?, etc. I discovered that if I type in Italian (that is there is at least one letter with accent) with the Sweave module selected lye is not able to correctly compile the document. I tried to change the input encoding, but it

Hello. I'm trying to find a way in R to calculate between and within subject variances and confidence intervals for some analytical method development data. I've found a reference to a method in Burdick, R. K. & Graybill, F. A. 1992, Confidence Intervals on variance components, CRC Press. This example is for Balanced Data confidence interval calculation from Pg 62. The data are

Dear all, I need to solve the following Lyapunov Matrix equation: C=ACA' + B, with A and B given square symmetric matrices. Does anyone knows of a package that can solve the lyapunov matrix equation in R? Or even a C/Fortran implementation? I did not find one on netlib. Thank you.

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 <-

Linearized array addresses are an issue in loop nest transformation. To alleviate the same, a multidimensional array indexing intrinsics have been proposed recently in the llvmp-dev mailing list [1]. From the mailing thread, it looks like there is a consensus on using intrinsics for communicating dimensions [2]. While working with our own loop transformation framework, we did a similar work on

After having spoken to Johannes, I think we had a classic misunderstanding on what "extending" means. 1. The most obvious why for me was changing GEP to allow variable-sized multi-dimensional arrays in the first argument, such as %1 = getelementptr double, double* %ptr, inrange i64 %i, inrange i64 %j (normally GEP would only allow a single index argument for a pointer-typed base

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'm a student doing my masters thesis and trying to work with S-Net version 1.0 (tool used for statistical analysis and visualizations of internet traffic) that is written in R. The problem is this: I have a perl script calling a function defined in an R script that is located in a directly different from where the perl script is. This gives the following error. >>> echo

Consider the following data frame X <- data.frame(Titanic) Does anyone know of an easy way to convert X into a multidimensional array? Example that doesn't work X <- as.array(X, dim=c(4,2,2,2)) To do what I need, X needs to be converted into an array of dimensions c(4,2,2,2) in this case, not a table. Thanks in advance.

Hi there I know, I'm sure you discussed this stuff 100 times, but I really have a basic understanding problem, if and how do I create a multidimensional array in R. I'm coming from MATLAB and there it's as easy as you ever could imagine. Ok, so, I want to have an array, where I can fill in data from a Excel spreadsheet. The array should be addressed like this:

I get some results back from running an iterative analysis in the form of a list of matrices. What I would like to do with this list is combine it such that all the similar components get combined into a multidimensional array. If possible I'd like to put results[[1]]$resultmean and results[[2]]$resultmean into a 3x3x2 array, and also put results[[1]]$resultsd and results[[2]]$resultsd in a

Hello, i want to create a multidimensional Array or Hash with group_by ''created_at''. 3 dimensions needed: myArray[week][day][data] currently i only created it with 2 dimesions: #model def self.group_per_day all.group_by{|t| t.created_at.strftime("%d. %B, %Y")}.sort #"%U" for Weeks end #controller @pdf_activities = Activity.group_per_day #view

Hello, Your way is much better than to mess with the dim attribute, like I did. But, "If you can create a data.frame or matrix that has the indices" Actually, it must be a matrix, indices can't be of type list. A way to avoid loops/apply altogether, and much faster, is the one creating K3 (K is the result from the op.) n <- 20 t2 <- system.time({ K2 <-

Hello. I have a 4 dimensional array and I want to fill in the slots with values which are a function of the inputs. Through searching the forums here I found that the function "outer" is helpful for 2x2 matrices but cannot be applied to general multidimensional arrays. Is there anything which can achieve, more efficiently than the following code, the job I want? K <-

i have a plain old array initialized like this: @columns = Array.new this array needs to be an array of arrays.. how do i tell ruby that this is an array of arrays? what i want to do is something like this: @columns[i] << ''some value'' where is is determined programattically.. obviously, ruby won''t let me do this since @columns[i] is not an array, but an

Hi, I was wondering if I could get some help on importing data into a three-dimensional array? I am importing data from several text files: dsdir<-"c:/documents and settings/desktop/07082008/" # path to files dsfb1<-"07082008-DI4129b.dat" # file base name firsthour<-13 # first hour of observation which changes from 6am to 1pm from day to day lasthour<-20 # last

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

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

Hi, I have a three dimensional array, e.g., my.array = array(0, dim=c(2,3,4), dimnames=list( d1=c("A1","A2"), d2=c("B1","B2","B3"), d3=c("C1","C2","C3","C4")) ) what I would like to get is then a dataframe: d1 d2 d3 value A1 B1 C1 0 A2 B1 C1 0 . . . A2 B3 C4 0 I'm sure there is one function to do

On Aug 2, 2019, at 8:57 AM, Michael Kruse <llvmdev at meinersbur.de> wrote: >> This is why I ask whether its makes sense to add this to LLVM IR: If you want HPC style loop transformations, I don’t think that LLVM IR itself will ever be great, even with this. This might make some narrow set of cases slightly better, but this is far from a solution, and isn’t contiguous with getting to