similar to: Varying results of package checks due to random seed

I have released a new, faster, version of R, which I call pqR (for "pretty quick" R), based on R-2.15.0. Among many other improvements, pqR supports automatic use of multiple cores to perform numerical computations in parallel with other numerical computations, and with the interpretive thread. It also implements a true reference counting scheme to reduce the amount of unnecessary

In testing pqR on Solaris SPARC systems, I have found two bugs that are also present in recent R Core versions. You can see the bugs and fixes at the following URLs: https://github.com/radfordneal/pqR/commit/739a4960a4d8f3a3b20cfc311518369576689f37 https://github.com/radfordneal/pqR/commit/339b7286c7b43dcc6b00e51515772f1d7dce7858 The first bug, in nls, is most likely to occur on a 64-bit

Dmitriy Selivanov (selivanov.dmitriy at gmail.com) wrote: > Consider following example: > > a = matrix(1:2, nrow = 2, dimnames = list(c("row1", "row2"), c("col1"))) > a[1, ] > # 1 > > It returns *unnamed* vector `1` where I would expect named vector. In fact > it returns named vector when number of columns is > 1. > Same issue applicable

On Tue, Jul 14, 2015 at 07:52:56PM -0400, Duncan Murdoch wrote: > On 14/07/2015 6:08 PM, Radford Neal wrote: > > In testing pqR on Solaris SPARC systems, I have found two bugs that > > are also present in recent R Core versions. You can see the bugs and > > fixes at the following URLs: > > > >

I think the discussion of this issue has gotten more complicated than necessary. First, there really is a bug. You can see this also by the fact that delayed warning messages are wrong. For instance, in R-3.1.2: > lapply(c(-1,2,-1),sqrt) [[1]] [1] NaN [[2]] [1] 1.414214 [[3]] [1] NaN Warning messages: 1: In FUN(c(-1, 2, -1)[[3L]], ...) : NaNs produced 2: In

A new version of pqR is now available at pqR-project.org, which fixes several bugs that are also present in the latest R Core patch release (r66002). A number of bugs found previously during pqR development are also unfixed in the latest R Core release. Here is the list of these bugs that are unfixed in r66002 (including documentation deficiencies), taken from the pqR bug fix and documentation

> On Fri, 2017-10-20 at 14:01 +0000, brodie gaslam via R-devel wrote: > > I'm thinking of this passage: > > > > > Logical values are sent as 0 (FALSE), 1 (TRUE) or INT_MIN = > > > -2147483648 (NA, but only if NAOK is true), and the compiled code > > > should return one of these three values. (Non-zero values other > > > than INT_MIN are

> ... with assignments inside of loops like this: > > reweight = function(iter, w, Q) { > for (i in 1:iter) { > wT = w * Q > } > } > ... before the RHS is executed, the LHS allocation would be added > to a small fixed length list of available space which is checked > before future allocations. If the same size is requested before the > next garbage

While doing some performance testing with the new version of pqR (see pqR-project.org), I've encountered an extreme, and quite unnecessary, inefficiency in the current R Core implementation of R, which I think you might want to correct. The inefficiency is in access to columns of a data frame, as in expressions such as df$col[i], which I think are very common (the alternatives of

I've been getting pqR to work on windows systems, and in the process have discovered various problems with R core versions of R and with Rtools. One is with the implementation of OpenMP in 64-bit Rtools. This problem is in Rtools215 and Rtools33, and presumably all the ones in between. You can see the problem with the following test program: #include <stdio.h> #include <omp.h>

41;309;0c> Why does debug() enter Browse[3] here at all, and why does it happen the > first time and not the second? This seems unexpected to me, and has > undesirable effects for ESS users (that I reported here - > https://stat.ethz.ch/pipermail/ess-help/2013-June/009154.html - but just > realized my post to r-devel didn't make it through when I tried to report > it back

Fellipe, CXXR development has moved to github, and we haven't fixed up the build for using git yet. Could you send a pull request with your change to the repo at https://github.com/cxxr-devel/cxxr/? Also, this patch may be useful for pqR too. https://github.com/radfordneal/pqR Thanks On Mon, Jan 19, 2015 at 2:35 PM, Dirk Eddelbuettel <edd at debian.org> wrote: > > On 19

> > The behaviour of a[1,] is unchanged, for backwards compatibility > > reasons. But in pqR one can explicitly mark an argument as > > missing using "_". When an array subscript is missing in this way, > > the names will not be dropped in this context even if there is > > only one of them. So a[1,_] will do what you want: > > > > > a =

On Wed, 18 Feb 2015, Nathan Kurz wrote: > On Wed, Feb 18, 2015 at 7:19 AM, Radford Neal <radford at cs.toronto.edu> wrote: >>> ... with assignments inside of loops like this: >>> >>> reweight = function(iter, w, Q) { >>> for (i in 1:iter) { >>> wT = w * Q >>> } >>> } >>> ... before the RHS is executed, the

On 14/07/2015 6:08 PM, Radford Neal wrote: > In testing pqR on Solaris SPARC systems, I have found two bugs that > are also present in recent R Core versions. You can see the bugs and > fixes at the following URLs: > > https://github.com/radfordneal/pqR/commit/739a4960a4d8f3a3b20cfc311518369576689f37 Thanks for the report. Just one followup on this one: There are two sections

> From: "Cohn, Robert S" <robert.s.cohn at intel.com> > > 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

Dear R forum I have a data.frame as cashflow_df = data.frame(instrument = c("ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC","ABC", "ABC", "PQR", "PQR",

> Henrik Bengtsson: > > I'm looking for a way to get the length of an object 'x' as given by > base data type without dispatching on class. The performance improvement you're looking for is implemented in the latest version of pqR (pqR-2016-10-24, see pqR-project.org), along with corresponding improvements in several other circumstances where unclass(x) does not

> From: Tomas Kalibera <tomas.kalibera at gmail.com> > > Thanks for the report, I am working on a patch that will address this. > > I confirm there is a lot of potential for speedup. On my system, > > 'N=200000; x <- substring(paste(rep("A", N), collapse=""), 1:N, 1:N)' > > spends 96% time in checking if the string is ascii and 3%

Suharto, If you're interested in performance with subscripting, you might want to look at pqR (pqR-project.org). It has some substantial performance improvements for subscripting over R Core versions. This is especially true for the current development version of pqR (probably leading to a new release in about a month). You can look at a somewhat-stable snapshot of recent pqR development