similar to: RE: [R] when can we expect Prof Tierney's compiled R?

If we are on the subject of byte compilation, let me bring a couple of examples which have been puzzling me for some time. I'd like to know a) if the compilation will likely to improve the performance for this type of computations, and b) at least roughly understand the reasons for the observed numbers, specifically why x[i]<- assignment is so much slower than x[i] extraction. The loops

> -----Original Message----- > From: Prof Brian Ripley [mailto:ripley@stats.ox.ac.uk] > Sent: Wednesday, April 27, 2005 1:13 AM > To: Vadim Ogranovich > Cc: Luke Tierney; r-devel@stat.math.ethz.ch > Subject: Re: [Rd] RE: [R] when can we expect Prof Tierney's > compiled R? > > On Tue, 26 Apr 2005, Vadim Ogranovich wrote: > ... > > The arithmetic shows

Hi I'm trying to set up a simulation problem without resorting to (m)any loops. I want to set entries in a data frame of zeros ('starts' in the code below) to 1 at certain points and the points have been randomly generated and stored in a separate data.frame ('sl'), which has the same number of columns. An example of the procedure is as follows: ml <-

Thanks for the reports. Will look into it soon and report back. Luke Sent from my iPhone > On Jan 3, 2019, at 2:15 PM, Martin Morgan <mtmorgan.bioc at gmail.com> wrote: > > For what it's worth this also introduced > >> df = data.frame(v = package_version("1.2")) >> rbind(df, df)$v > [[1]] > [1] 1 2 > > [[2]] > [1] 1 2

I am excited to learn that Prof. Tierney is bringing to us compiled R. I would like to learn when it will be available. This information will be useful in scheduling some of my projects. Thanks. Jason Jason Liao, http://www.geocities.com/jg_liao Dept. of Biostatistics, http://www2.umdnj.edu/bmtrxweb University of Medicine and Dentistry of New Jersey 683 Hoes Lane West, Piscataway‚ NJ 08854

When building R-devel with gcc 5.2.0 (mingw-w64 v4) on Windows, make check fails reg-tests-1b.R at the following check: x <- c(1:2, NA) sx <- sd(x) !is.nan(sx) Here 'sx' should be 'NA' but it is 'NaN'. It turns out this problem only appears when the function is byte compiled with optimization level 3: mysd <- function (x, na.rm = FALSE) sqrt(var(if

On Thu, Jan 22, 2015 at 11:44 AM, <luke-tierney at uiowa.edu> wrote: > I'm not convinced that how to make :: faster is the right question. If > you are finding foo::bar being called often enough to matter to your > overall performance then to me the question is: why are you calling > foo::bar more than once? Making :: a bit faster by making it a > primitive will remove

I noticed some problems that cropped in the latest versions of R-devel (2016-11-08 r71639 in my case) for one of my packages. I _think_ I have narrowed it down to the changes to what gets byte-compiled by default. The following example run illustrates the problem I'm having: compiler::enableJIT(0) fun <- function(x) local(as.list(parent.frame(2))) fun(1) ## $x ## [1] 1 ##

Dear All, In R 3.4.2 (Linux), the compiler seems to have regressed: $ R --vanilla g = function() { N = 1e7; ans = numeric(N) system.time({for (j in 1:N) ans[j] = 1}) } g() # user system elapsed # 4.272 0.000 4.272 g1 = compiler::cmpfun(g) g1() # user system elapsed # 4.232 0.004 4.235 Running the above code in Windows 3.3.1, g() takes the same time, but g1() takes around 0.5

I believe the issue is that on Windows the sqrt function when called with a NaN does not return the same NaN, as it does on other platforms. We have #if (defined(_WIN32) || defined(_WIN64)) && defined(__GNUC__) && \ __GNUC__ <= 4 # define R_sqrt(x) (ISNAN(x) ? x : sqrt(x)) #else # define R_sqrt sqrt #endif for implementing the SQRT opcode. I suspect this came from Duncan

Should be fixed in r75946. Best, luke On Fri, 4 Jan 2019, Tierney, Luke wrote: > Thanks for the reports. Will look into it soon and report back. > > Luke > > Sent from my iPhone > >> On Jan 3, 2019, at 2:15 PM, Martin Morgan <mtmorgan.bioc at gmail.com> wrote: >> >> For what it's worth this also introduced >> >>> df = data.frame(v =

Ralf I don't doubt this is expected with the current implementation, I doubt the implementation is desirable. Suggesting to turn this to pbirthday(1e6, classes = 2^53) ## [1] 5.550956e-05 (which is still non-zero, but much less likely to cause confusion.) Best regards Kirill On 26.02.19 10:18, Ralf Stubner wrote: > Kirill, > > I think some level of collision is actually

Hi, I'm running into a case where byte-compilation changes the semantic of a function. This is with R 3.4.0: foo <- function(x) { TRUE && x } foo(c(a=FALSE)) # [1] FALSE # OK foo(c(a=TRUE)) # [1] TRUE # OK foo(c(a=FALSE)) # a # ???? # FALSE The 3rd call returned a result that it different from the 1st call! After

Hello, given that `*tmp*` is removed after a replacement, how can code like this work? Is there some special handling for a variable named `*tmp*` when it comes to make element assignments? > x<-c(1,2) > x[1]<-42 > `*tmp*`[1]<-7 # I would expect this one to fail > `*tmp*` Error: object '*tmp*' not found Confused greetings, Michael -- Dr. Michael Haupt Principal

Gabe As mentioned on Twitter, I think the following behavior should be fixed as part of the upcoming changes: R.version.string ## [1] "R Under development (unstable) (2019-02-25 r76160)" .Machine$double.digits ## [1] 53 set.seed(123) RNGkind() ## [1] "Mersenne-Twister" "Inversion"??????? "Rejection" length(table(runif(1e6))) ## [1] 999863 I don't

Ah, with R 3.5.0 or R 3.4.2, but not with R 3.3.1, 'eval' inside 'for' makes compiled version behave like non-compiled version. options(error = expression(NULL)) library(compiler) enableJIT(0) f <- function(x) for (i in 1) {x; eval(expression(i))} f(is.numeric(y)) # Error: object 'y' not found fc <- cmpfun(f) fc(is.numeric(y)) # Error: object 'y' not found

Hello, Due to exploration of the JIT capabilities offered through the {compiler} package, I came by the fact that using enableJIT(2) can *slow* the rpart function (from the {rpart} package) by a magnitude of about 10 times. Here is an example code to run: library(rpart) require(compiler) enableJIT(0) # just making sure that JIT is off # We could also use enableJIT(1) and it would be fine fo

On Mon, 1 Apr 2019, Martin Maechler wrote: >>>>>> Suharto Anggono Suharto Anggono via R-devel >>>>>> on Sun, 31 Mar 2019 15:26:13 +0000 writes: > > > Ah, with R 3.5.0 or R 3.4.2, but not with R 3.3.1, 'eval' > > inside 'for' makes compiled version behave like > > non-compiled version. > > Ah.. ... thank

>>>>> luke-tierney >>>>> on Tue, 8 Sep 2020 09:42:43 -0500 (CDT) writes: > On Tue, 8 Sep 2020, Martin Maechler wrote: >>>>>>> Martin Maechler >>>>>>> on Tue, 8 Sep 2020 10:40:24 +0200 writes: >> >>>>>>> Hugh Parsonage >>>>>>> on Tue, 8 Sep 2020

Thanks for the report. Fixed in R_devel with r72631; I'll port to R-patched later today or tomorrow. The default setting and how to get the current settings are documented in the Details section of the enableJIT help page at the end of the paragraph for enableJIT. Best, luke On Wed, 26 Apr 2017, Herv? Pag?s wrote: > Hi, > > I'm running into a case where byte-compilation