similar to: Conditional cumulative sum

Hi, I have a general question on LoopUnswtich pass. Consider the following IR snippet: define i32 @test(i1 %cond) { br label %loop_begin loop_begin: br i1 %cond, label %loop_body, label %loop_exit loop_body: br label %do_something do_something: call void @some_func() noreturn nounwind br label %loop_begin loop_exit: ret i32 0 } declare void @some_func() noreturn After running

Dear R-Users, I would like to know whether it is possible to draw several stacked barplots (i.e. side by side on the same sheet)... my data look like : Cond1 Cond1' Cond2 Cond2' Compartment 1 11,81 2,05 12,49 0,70 Compartment 2 10,51 1,98 13,56 0,85 Compartment 3 1,95 0,63 2,81 0,22 Compartment 4 2,08 0,17

I changed the input C to using a 64 bit type for the loop index (this eliminates 'sext' instructions in the IR) Here the IR produced with clang -O0 define float @foo(i64 %start, i64 %end, float* %A) #0 { entry: %start.addr = alloca i64, align 8 %end.addr = alloca i64, align 8 %A.addr = alloca float*, align 8 %sum = alloca [4 x float], align 16 %i = alloca i64, align 8

Hi everyone, I'm having some trouble with my ifelse statements. I'm trying to put 12 conditions within 3 groups. Here is the code I have so far: dat$cond <- ifelse(test = dat$cond == "cond1" | dat$cond == "cond2" | dat$cond == "cond3" dat$cond == "cond4" yes = "Uniform" no = ifelse(test =

In PR 22718, we are looking at issues with long running applications producing non-representative frequencies. For example, in these two loops: int g = 0; __attribute__((noinline)) void bar() { g++; } extern int printf(const char*, ...); int main() { int i, j, k; for (i = 0; i < 1000000; i++) bar(); printf ("g = %d\n", g); g = 0; for (i = 0; i < 500000; i++)

Not a reproducible example, so a bit of guessing here, but a) don't try to assign results to variables inside the ifelse. That is, remove all the single-equals signs and "test" variables. If you really need to conditionally assign variables then use "if"... but chances are good you don't need that. b) "closure" is effectively another word

Hi All, I'm planning to submit my first package to R, and although I read all the documentation, I'm not very clear on the following 2 items, from which I'd appreciate your guidance: 1)I understand it is suggested to use the R dev version to build the package. Which one specifically should I use to build a package on a Mac OS? How about package dependencies, which version should I

I am trying my luck on this global reduction kernel: float foo( int start , int end , float * A ) { float sum[4] = {0.,0.,0.,0.}; for (int i = start ; i < end ; ++i ) { for (int q = 0 ; q < 4 ; ++q ) sum[q] += A[i*4+q]; } return sum[0]+sum[1]+sum[2]+sum[3]; } LV: Checking a loop in "foo" LV: Found a loop: for.cond1 LV: Found an induction variable. LV: We

Hi All, I didn't have much success through my Google search in finding any active R-related projects to create a wrapper around TensorFlow in R. Anyone know if this is on the go? Thanks, Axel. [[alternative HTML version deleted]]

Hi All, I didn't have much success through my Google search in finding any active R-related projects to create a wrapper around TensorFlow in R. Anyone know if this is on the go? Thanks, Axel. [[alternative HTML version deleted]]

Dear List, The gbm package on Win 7 produces different results for the relative importance of input variables in R 32-bit relative to R 64-bit. Any idea why? Any idea which one is correct? Based on this example, it looks like the relative importance of 2 perfectly correlated predictors is "diluted" by half in 32-bit, whereas in 64-bit, one of these predictors gets all the importance

Dear List, I'm trying to solve this simple optimization problem in R. The parameters are the exponents to the matrix mm. The constraints specify that each row of the parameter matrix should sum to 1 and their product to 0. I don't understand why the constraints are not satisfied at the solution. I must be misinterpreting how to specify the constrains somehow. library(alabama) ff <-

Dear R users, I know this issue came up in the list several times. I’m currently running R on 32-bit on Windows and due to memory limitation problems would like to move to a 64-bit environment. I’m exploring my options and would appreciate your expertise: 1) Windows 64-bit: Prof. Brian Ripley recently posted the experimental built of R for win 64-bit. I’ll appreciate any feedback on

Dear R users, I have a matrix a and a classification vector b such that > str(a) num [1:50, 1:800000] and > str(b) Factor w/ 3 levels "cond1","cond2","cond3" I'd like to do an anova on all 800000 columns and record the F statistic for each test; I currently do this using f.stat.vec <- numeric(length(a[1,]) for (i in 1:length(a[1,]) { f.test.frame

Dear List, I'm trying to add a function that calls a Shiny App in my R package. The issue is that within my function, I'm creating objects that I'd like to pass to the app. For instance, from the example below, I'm getting "Error: object 'xs' not found". How can I pass "xs" explicitly to shinyApp()? *Under R directory:* myApp <- function(x, ...) {

Hi, I'm looking to move from Windows into a 64-bit Linux environment. Which is the best Linux Flavor to use within R? To install R on this environment, do I need to do any compiling? Thanks all! Axel. [[alternative HTML version deleted]]

Dear Axel, I've used environment for such problems. assign("xs", xs, envir = my.env) in the myApp function get("xs", envir = my.env) in the server function Best regards, ir. Thierry Onkelinx Statisticus/ Statiscian Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie &

Dear list, For a reason it would take me long to explain, I need to do something along the lines of what's shown below -- i.e., create an object from dplyr::summarise, and then evaluate it on a data frame. I know I could directly do: df %>% dplyr::summarise(x1_mean = mean(x1)) but this is not what I'm looking for. library(dplyr) df <- data.frame(x1 = rnorm(100), x2 =

Dear List, This is an embarrassing question, but I can seem to make this work…How do I change the font size on the xlab and on the numbers shown in the x-axis on the time series plot below. The arguments cex.lab and cex.axis do not seem to be 'passing' to the plot function. plot(ts(rnorm(100), start=2004, freq=12), ylab="RQI", xlab="My X lab",

Dear List, I have a wrapper function that creates a Shiny App, as illustrated below. I'd like to include the function myApp() inside a package. I'd appreciate your guidance here, as I could not find good instructions on this online. myApp <- function(x) { require(shiny) shinyApp( ui = fluidPage( sidebarLayout( sidebarPanel(sliderInput("n",