similar to: storing data from database into array

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 <-

Intrinsics can return `llvm_any_ty` (Intrinsics.td). In that case the return type is added as a suffix to the intrinsic's name, i.e. the syntax in the RFC is not 100% the syntax for intrinsics. Same for the parameters which each must have their types explicitly mentioned. Michael Am Mo., 22. Juli 2019 um 19:08 Uhr schrieb Kaylor, Andrew <andrew.kaylor at intel.com>: > > Is it

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'm having trouble getting Samba working on Solaris 10 with a large active directory (35000 users, 5000 groups). I've set this up successfully in the past with winbind enum users = yes and winbind enum users = yes in the smb.conf file. Owing to the large number of users in this application, I need to have these set to no. Realistically, only a couple dozen people and 3 groups actually

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.

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

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

On Wed, Jun 23, 2010 at 12:22 AM, Michael Spencer <bigcheesegs at gmail.com> wrote: > I'm now going to make the stub patches that Daniel requested. Added llvm/Support/COFF.h and merged in COFF constants from llvm/MC/MCSectionCOFF.h. Zeroth patch is done. http://github.com/Bigcheese/llvm-mirror/commit/2d88aa08a072bb5f8d687b67d1476f23d37a87d4 A svn-style patch against svn HEAD is

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

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

An updated version of the package plink has been uploaded to CRAN. This is a major revision that now includes multidimensional models and methods. plink is a package for conducting unidimensional and multidimensional IRT-based test linking using separate calibration methods for multiple groups for single-format or mixed-format common items. The package supports sixteen IRT models and eleven

An updated version of the package plink has been uploaded to CRAN. This is a major revision that now includes multidimensional models and methods. plink is a package for conducting unidimensional and multidimensional IRT-based test linking using separate calibration methods for multiple groups for single-format or mixed-format common items. The package supports sixteen IRT models and eleven

> 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 that you're interested in to be worth optimizing for? Yes - at least in Chapel (which is one of the motivating languages) these are very common. In other words, typical

Hi there, I'm trying to do a regression experiment on a multidimensional dataset where both x and y in the model are multidimensional vectors. I'm using R version 2.9.2, updated packages, on a Linux box. I've tried gausspr(), ksvm() and rvm(), and the models are computed fine, but I'm always getting the same error message when I try to use predict(): "Error in

We could also simply extend the existing inrange mechanism to non-constantexpr GEPs.  It would remove an inconsistency in the semantics, be relatively straight forward, and solve the motivating example. (I didn't read the proposal in full, so there may be other examples it doesn't solve.) Philip On 7/22/19 10:01 AM, Peter Collingbourne via llvm-dev wrote: > The restrictions of

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".

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

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