similar to: robustbase compilation problem: probably boneheaded? maybe 32-bit?

A recent R devel NEWS item: approx(), spline(), splinefun() and approxfun() also work for long vectors. In current R devel, in function 'approx1' in src/library/stats/src/approx.c and in function 'spline_eval' in src/library/stats/splines.c, in #ifdef LONG_VECTOR_SUPPORT there is a comment "R_xlen_t is double". It is incorrect. In Rinternals.h, in #ifdef

On Fri, 10 Feb 2023 23:38:55 -0600 Spencer Graves <spencer.graves at prodsyse.com> wrote: > I have a 4.54 GB file that I'm trying to read in chunks using > "scan(..., skip=__)". It works as expected for small values of > "skip" but goes into an infinite loop for "skip=1e11" and similar > large values of skip: I cannot even interrupt it; I

Hi all, I found an unexpected behavior when I was trying to use the macro defined in "R_ext/Itermacros.h" to loop over an atomic vector. Here is a minimum example: C++ code ``` #include "R_ext/Itermacros.h" #define GET_REGION_BUFSIZE 2 //Redefine the macro since C++ is not happy with the implicit type conversion #define ITERATE_BY_REGION_PARTIAL(sx, px, idx, nb, etype,

On 10/25/19 11:01 AM, Tomas Kalibera wrote: > On 10/23/19 6:45 AM, Wang Jiefei wrote: >> Hi all, >> >> I found an unexpected behavior when I was trying to use the macro >> defined >> in "R_ext/Itermacros.h"? to loop over an atomic vector. Here is a >> minimum >> example: >> >> C++ code >> ``` >> #include

I'm observing that base::sum(x, na.rm=FALSE) for typeof(x) == "double" is much more time consuming when there are missing values versus when there are not. I'm observing this on both Window and Linux, but it's quite surprising to me. Currently, my main suspect is settings in on how R was built. The second suspect is my brain. I hope that someone can clarify the below

Is there a missing value constant defined for R_xlen_t, cf. NA_INTEGER (== R_NaInt == INT_MIN) for int(eger)? If not, is it correct to assume that missing values should be taken care/tested for before coercing from int or double? Thank you, Henrik

Le 19/04/2018 ? 09:30, Tomas Kalibera a ?crit?: > On 04/19/2018 02:06 AM, Duncan Murdoch wrote: >> On 18/04/2018 5:08 PM, Tousey, Colton wrote: >>> Hello, >>> >>> I want to report a bug in R that is limiting my capabilities to >>> export a matrix with write.csv or write.table with over >>> 2,147,483,648 elements (C's int limit). I found

Sorry for post a lot of things, for the first part of code, I copied my C++ iter macro by mistake(and you can see an explicit type casting). Here is the macro definition from R_exts/Itermacros.h #define ITERATE_BY_REGION_PARTIAL(sx, px, idx, nb, etype, vtype, \ strt, nfull, expr) do { \ * const** etype *px = DATAPTR_OR_NULL(sx); *

Hi Bob, Thanks for sending around the link to that. It looks mostly right and looks like a useful onramp. There are a few things to watch out for though (I've cc'ed Romain so he's aware of these comments). @romain I hope you taake the following comments as they are intended, as help rather than attacks. The largest issue I see is that the contract for Get_region is that it *populates

Hi Tomas, Can you share the full code for your benchmark, compiler options, and performance results so that I can try to reproduce them? There are a lot of variables that can affect the results. Private email is fine if it is too much for the mailing list. I am measuring on Knight's Landing (KNL) that was released in November. KNL is not a co-processor so no offload is necessary. R executes

Hello everyone When asking to create sequence longer than 2^48 (which is forbidden) the same error message appears translated and untranslated depending on whether R_XLEN_T_MAX is reached or exceeded while not an error o problem beyond that of the untranslated text, i find this weird. ?could it be fixed in any manner? R_XLEN_T_MAX <- 4503599627370496 > length(1:(R_XLEN_T_MAX - 1)) [1]

I am using R to multiply some large (30k x 30k double) matrices on a 64 core machine (xeon phi). I added some timers to src/main/array.c to see where the time is going. All of the time is being spent in the matprod function, most of that time is spent in dgemm. 15 seconds is in matprod in some code that is checking if there are NaNs. > system.time (C <- B %*% A) nancheck: wall time

> Do you have R code (including set.seed(.) if relevant) to show on how to generate > the large square matrices you've mentioned in the beginning? So we get to some > reproducible benchmarks? Hi Martin, Here is the program I used. I only generate 2 random numbers and reuse them to make the benchmark run faster. Let me know if there is something I can do to help--alternate

>>>>> Jan van der Laan <rhelp at eoos.dds.nl> >>>>> on Fri, 6 Oct 2017 12:13:39 +0200 writes: > It is actually model.matrix that crashes, not glm. Same > crash occurs with e.g. lm. > model.matrix(dob_mon ~ dob_day*dob_mon, data = tab) > also crashes R. Yes, segmentation fault. It only happens when these are *logical*

On 18/04/2018 5:08 PM, Tousey, Colton wrote: > Hello, > > I want to report a bug in R that is limiting my capabilities to export a matrix with write.csv or write.table with over 2,147,483,648 elements (C's int limit). I found this bug already reported about before: https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17182. However, there appears to be no solution or fixes in upcoming

Thanks Brodie, that's some nice detective work. If someone wanted to grant me access to Bugzilla, I'll be happy to post the bug and patch there (with your permission Brodie?) and help this bug get fixed. Mike. On Tue., 25 Sep. 2018, 10:53 pm brodie gaslam, <brodie.gaslam at yahoo.com> wrote: > > > For what it's worth the following patch fixes that particular problem

On 2nd thought, I think a better fix to the segfault is something like this: --- a/src/main/memory.c +++ b/src/main/memory.c @@ -3444,6 +3444,8 @@ R_xlen_t (XTRUELENGTH)(SEXP x) { return XTRUELENGTH(CHK2(x)); } int (IS_LONG_VEC)(SEXP x) { return IS_LONG_VEC(CHK2(x)); } const char *(R_CHAR)(SEXP x) { + if(!x) + error("de-referncing null. Check the validity of your data.");

I believe the performance of isUnsorted() in sort.c could be improved by calling REAL() once (outside of the for loop), rather than calling it twice inside the loop. As an aside, it is implemented in the faster way in doSort() (sort.c line 401). The example below shows the performance improvement for a vectors of double of moving REAL() outside the for loop. # example as implemented in

In do_matrix in src/array.c there is a type switch containing : case LGLSXP : for (i = 0; i < nr; i++) for (j = 0; j < nc; j++) LOGICAL(ans)[i + j * NR] = NA_LOGICAL; That seems page inefficient, iiuc. Think it should be : case LGLSXP : for (j = 0; j < nc; j++) for (i = 0; i < nr; i++) LOGICAL(ans)[i + j * NR] = NA_LOGICAL; or more simply : case

On Sep 20, 2015, at 3:06 PM, Henrik Bengtsson <henrik.bengtsson at ucsf.edu> wrote: > Is there a missing value constant defined for R_xlen_t, cf. NA_INTEGER > (== R_NaInt == INT_MIN) for int(eger)? If not, is it correct to > assume that missing values should be taken care/tested for before > coercing from int or double? > R_xlen_t is type of the vector length (see