similar to: Save debugging session info and resume from the middle?

The reimplemented APIs are: * list_devices * list_partitions * part_to_dev * part_to_partnum * is_whole_device --- daemon/Makefile.am | 2 + daemon/daemon.h | 3 - daemon/devsparts.c | 257 ---------------------------------------------- daemon/devsparts.ml | 109 ++++++++++++++++++++ daemon/devsparts.mli | 25 +++++ daemon/guestfsd.c | 75

Function/file names are hypothetical. Say I have written myfunction.R, which calls myfunction.c via .C("myfunction", ...). I've compiled successfully myfunction.c via R CMD SHLIB myfunction.c in the terminal. Then, in the R console: dyn.load("myfunction.so") source("myfunction.R") test <- myfunction() # works fine So everything is in order, myfunction works

Hi everyone, I made some tests with Rcmdr, to add a function with default parameters : For example (very simple): myfunction<-function(var="314"){ print("hello") print(var) } if I run myfunction() directly i see : > myfunction() [1] "hello" [1] "314" it's ok. But if i edit de Rcmdr-menu.txt (in

I have a function myFunction(beta,x) where beta is a vector of coefficients and x is a data frame (think of it as a matrix). I want to optimize the function myFunction() by ONLY changing beta, i.e. x stays constant, with 4 constraints. I have the following code (with a separate source file for the function): rm(list=ls()) source('mySourceFile')

Dear R helpers, I have what another member on this forum described as an embarrassingly parallel problem. I am trying to fit models on subsets of some data based on unique combinations of two id factors in the dataset. Total number of combinations is 30^5, and this takes a long time. So, I would like fit models for each of the datasets produced by subsetting on the unique combinations, splitting

Hello R-List, ** This e-mail was initially bounced. Please forgive any duplicates.** I'm creating a new generic function and 3 associated methods, in which each of the methods only needs a subset of the arguments specified in the generic. So, I create the generic like so (with the signature defaulting to all of the args) ... setGeneric( name="myFunction", def =

R-developers Does anybody know how I incorporate the use of the tracker in RUnit in the unit tests? I have read the RUnit Vignette, help pages and searched around, but I could find no examples of using 'inspect' in the unit test functions. Moreover, doing so, I tried something like library(RUnit) myFunction <- function(x) { return(x) } track <- tracker() track$init()

Hello, everyone, I encounter a strange problem about llvm type i64 and C++ type int64_t. I instrumented a program to call the function 'myFunction' in the C++ shared library. 'myFunction' is something like this: int64_t myFunction() { int64_t retValue; ... std::cout << "retValue: " << retValue << "\n"; return retValue; }

Hi all, I have a function - let's call it "myfunction". This function is based on some random number generator. Now, once in a while the function will break/crash depending on the random number it generate inside the function. To avoid the problem, what I intend to do is the following: 1. Catch the try-error using class. 2. Redo the function if it returns "try-error" 3.

On 09/08/2018 5:45 PM, Abs Spurdle wrote: > I apologize if this issue has been raised before. > > I really like object oriented S3 programming. > However, there's one feature of object oriented S3 programming that I don't > like. > Generic functions can have arguments other than dots. > > Lets say you have an R package with something like: > >

Hello, I've got a function that takes a numeric vector (x), computes a transformation value (myAttr) for x, transforms x according to myAttr and then sets myAttr as an attribute of x before returning x, so I can easily know what myAttr was used (basically it's a power transformation and myAttr is the lambda). myFunction.numeric <- function(x, ...) { myAttr <- calcMyAttr(x, ...) x

Dear listers: As a part of a intermediate process, I need to use and modify a very big matrix (some 30000x30000) inside the body of a function. If the matrix is defined in the function, R shows a error message "Cannot allocate vector of size 6.7 Gb". But if I define the matrix before the function is called (as soon as the dimension can be calculated) R can allocate it. The problem is

Dear All, I hope you don't mind helping me with this small issue. I haven't been using R in years and I'm trying to fill in a matrix with the output of a function (I'm probably using the Matlab logic here and it's not working). Here is my code: for (i in 1:length(input)){ out[i,1:3] <- MyFunction(input[i,1],input[i,2], input[i,3]) out[i,4:6] <-

Dear all, I have the following problem: I have written a function genereating to plots, eg myfunction <- (data, some.parameters) { #some calculations etc . par (mfrow=c(1,2)) plot1(......) plot2(.....) } which works fine. But for analysing several variants, I tried a slope, eg: par (mfrow=c(5,5)) for ( i in 1:10) { myfunction(data, i) } Off

Dear all, Does R offer a means by which a function can determine whether its return value is assigned? I am using R 2.4.1 for Windows. Suppose what I am looking for is called "return.value.assigned". Then one might use it like this myfunction <- function () { # Create bigobject here if (return.value.assigned()) { bigobject } else {

LGTM. I think you can sent patch and let the ball rolling! I would like to review it. ;) 2018-03-28 10:41 GMT+08:00 Hsiangkai Wang via llvm-dev <llvm-dev at lists.llvm.org>: > Hello all, > > I would like to enhance LLVM debug info that supports setting > breakpoint on labels in function. > > Generally, if users use GDB as their debugger, they could set > breakpoints on

I am working on minimization of sum of squared errors for a problem that has 2 box-constrained parameters. I got the solution for this problem using "L-BFGS-B" method in optim function using an R code as res<-optim(par=c(parInit), fn=myFunction, method = c("L-BFGS-B"), lower = parMin, upper = parMax,

Sounds good to me. You can also see llvm.codeview.annotation which does a similar thing, but it is modeled as having internal, invisible side effects. These should stay separate, but it may provide a guide for implementation. On Tue, Mar 27, 2018 at 7:41 PM Hsiangkai Wang via llvm-dev < llvm-dev at lists.llvm.org> wrote: > Hello all, > > I would like to enhance LLVM debug info

I am interested in running R commands asynchronously. My first choice is in the same R session that I am currently in. Here, the goal would be to run something like RunAsynchSameSession(myfunction(), "outputname.rda") Once RunAsynchSameSession had started myfunction(), RunAsynchSameSession would complete immediately. myfunction would keep going. It is OK if execution of the

Hi, Firstly I am very new to Ruby on Rails but think its fantastic! :o) I am trying to figure out how I can call multiple functions from the drop_receiving_element :complete. I have the following code in my index.rhtml and it works fine. It calls the javascript function "additem" that is on the page. <%= drop_receiving_element "dcwindow", :update =>