similar to: New version of the R parser in pqR

> maybe there?s a reason for it, but the discrepancy between the > handling of `[` and `$` in deparsing seems odd to me: > > > substitute(a[1], list(a = quote(x * y))) > x * y[1] > > > substitute(a$b, list(a = quote(x * y))) > (x * y)$b > > The former is still executed in the right order (`*` first, then > `[`), which is not what you?d expect looking at the

I will shortly be releasing a new version of pqR (you can get a test version from pqR-project.org now - scroll to the bottom of the page). One new feature in this version requires adding a bit to the flags written out when data is serialized. I thought I'd let you know about this so as to avoid any possible conflicts. The new feature is that a few R objects are defined as constants, which

> 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

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

> 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%

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

Regarding the discussion of getting length(unclass(x)) without an unclassed version of x being created... There are already no copies done for length(unclass(x)) in pqR (current version of 2017-06-09 at pqR-project.org, as well as the soon-to-be-release new version). This is part of a more general facility for avoiding copies from unclass in other circumstances as well - eg,

There are websites using python to convert a pdb to a pqr. I was wondering if there is a simpler way to do it. We have a protein in pdb format, and want to convert that to a pqr file so that the program apbs can open it. We want to accomplish this conversion in R. Thank you for your help. -- View this message in context: http://n4.nabble.com/Converting-pdb-to-pqr-tp1475426p1475426.html Sent

I am trying to write a program that uses R and takes a pdb file, and converts it to a pqr file. This task is simple generally, using the website, http://pdb2pqr-1.wustl.edu/pdb2pqr/. How do you use R to input a pdb file (that is on hand) into the upload pdb file input, and run the website and give the return file to be a pqr file. Thanks for your help. -- View this message in context:

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

> 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

Hello I was reading the source main/src/gram.y and had one question, how does R parse x = 1 According the grammar: prog : END_OF_INPUT { return 0; } | '\n' { return xxvalue(NULL,2,NULL); } | expr_or_assign '\n' { return xxvalue($1,3,&@1); } | expr_or_assign ';' { return xxvalue($1,4,&@1); } | error { YYABORT; } ; So this should be of the 3rd

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

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

Along with getting pqR to work on Windows, I've also been testing it in the context of embedded R, and in the process have found some problems with the examples given of embedded R use. One problem can be seen in R_ReplDLLinit, in src/main/main.c: void R_ReplDLLinit(void) { SETJMP(R_Toplevel.cjmpbuf); R_GlobalContext = R_ToplevelContext = R_SessionContext = &R_Toplevel;

> From: "Pavel S. Ruzankin" <ruzankin at math.nsc.ru> > Let us consider the current uniform sampling without replacement > algorithm. It resides in function do_sample in > https://svn.r-project.org/R/trunk/src/main/random.c > Its complexity is obviously O(n), where the sample is selected from > 1...n, since the algorithm has to create a vector of length n. So

On Sun, 1 Mar 2015, Radford Neal wrote: > I think the discussion of this issue has gotten more complicated than > necessary. The discussion has gotten no more complicated than it needs to be. There are other instances, such as Reduce where there is a bug report pending that amounts to the same issue. Performing surgery on expressions and calling eval is not good practice at the R level

I have just committed (in r59883) some changes to the R parser based on Romain Francois' parser package. Packages that made use of parser will hopefully find that the information in base R gives them what they need to work with, but the data is not identical to what parser recorded (since it was not consistent with some things already in R). One reason for the change was that the parser

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: > > > >

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