similar to: read.csv quadratic time in number of columns

Dear R-devel, I did a systematic comparison of write.csv with similar functions, and observed two asymptotic inefficiencies that could be improved. 1. write.csv is quadratic time (N^2) in the number of columns N. Can write.csv be improved to use a linear time algorithm, so it can handle CSV files with larger numbers of columns? For more details including figures and session info, please see

On 2/20/19 7:55 PM, Toby Hocking wrote: > Update: I have observed that stringi::stri_sub is linear time complexity, > and it computes the same thing as base::substring. figure > https://github.com/tdhock/namedCapture-article/blob/master/figure-substring-bug.png > source: > https://github.com/tdhock/namedCapture-article/blob/master/figure-substring-bug.R > > To me this is a

Update: I have observed that stringi::stri_sub is linear time complexity, and it computes the same thing as base::substring. figure https://github.com/tdhock/namedCapture-article/blob/master/figure-substring-bug.png source: https://github.com/tdhock/namedCapture-article/blob/master/figure-substring-bug.R To me this is a clear indication of a bug in substring, but again it would be nice to have

Hi all, (and especially hi to Tomas Kalibera who accepted my patch sent yesterday) I believe that I have found another bug, this time in the substring function. The use case that I am concerned with is when there is a single (character scalar) text/subject, and many substrings to extract. For example substring("AAAA", 1:4, 1:4) or more generally, N=1000

Hi all, Several people have noticed that gregexpr is very slow for large subject strings when perl=TRUE is specified. - https://stackoverflow.com/questions/31216299/r-faster-gregexpr-for-very-large-strings - http://r.789695.n4.nabble.com/strsplit-perl-TRUE-gregexpr-perl-TRUE-very-slow-for-long-strings-td4727902.html - https://stat.ethz.ch/pipermail/r-help/2008-October/178451.html I figured out

Hi R-core, I have been performance testing R packages for wide-to-tall data reshaping and for the most part I see they differ by constant factors. However in one test, which involves converting into multiple output columns, I see that stats::reshape is in fact quadratic in the number of input columns. For example take the iris data, which has 4 input columns to reshape, and the desired output

Hello, I've been using R for about 3 years now and I'm pretty sure this is a bug. I'm using R 2.2.0. The way R is set up to get packages from CRAN using install.packages is really convenient --- if you are installing to your system's main package directory. However, I observe the following problem: I want package X but it requires package Y. Further, I have neither package

Well it's only a leak if you don't get the memory back after it returns, right? Anyway, one (untested by me) possibility is the copying of memory pages when the garbage collector touches objects, as pointed out by Radford Neal here: http://r.789695.n4.nabble.com/Re-R-devel-Digest-Vol-149-Issue-22-td4710367.html If so, I don't think this would be easily avoidable, but there may be

Toby, > On Sep 2, 2015, at 1:12 PM, Toby Hocking <tdhock5 at gmail.com> wrote: > > Dear R-devel, > > I am running mclapply with many iterations over a function that modifies > nothing and makes no copies of anything. It is taking up a lot of memory, > so it seems to me like this is a bug. Should I post this to > bugs.r-project.org? > > A minimal reproducible

It is known, with a known workaround, see e.g. https://www.stats.ox.ac.uk/pub/bdr/memtests/README.txt . Set suppressions in ~/.valgrindrc, e.g. the CRAN check machine has --suppressions=/data/blackswan/ripley/wcsrtombs.supp It is an issue in your OS (glibc), not TRE nor R. On 10/06/2020 00:21, Toby Hocking wrote: > Hi all, > > I'm on Ubuntu 18.04, running R-4.0.0 which I

Hi Toby, AFAIK it has not been addressed in R. You can handle the problem on your package side, see https://github.com/Rdatatable/data.table/pull/3237 Regards, Jan On Thu, May 30, 2019 at 4:46 AM Toby Hocking <tdhock5 at gmail.com> wrote: > > Hi all, > > I am having an issue related to installing packages on windows with > R-3.6.0. When installing a package that is in use, I

Dear R-devel, I am running mclapply with many iterations over a function that modifies nothing and makes no copies of anything. It is taking up a lot of memory, so it seems to me like this is a bug. Should I post this to bugs.r-project.org? A minimal reproducible example can be obtained by first starting a memory monitoring program such as htop, and then executing the following code while

Hi Toby, As Gabor pointed out the place where the various levers R CMD check supports is in the R-internals manual, but there is a link directly to that section in https://cloud.r-project.org/doc/manuals/r-release/R-exts.html#Checking-packages It could perhaps be more prominent, perhaps by moving the paragraph that appears in to before the detailed list of exact tests that are performed?

Hi all, I'm on Ubuntu 18.04, running R-4.0.0 which I compiled from source, and using valgrind I am always seeing the following message. Does anybody else see that? Is that a known false positive? Any ideas how to fix/suppress? Seems related to TRE, do I need to upgrade that? (base) tdhock at maude-MacBookPro:~/R/binsegRcpp$ R --vanilla -d valgrind -e 'extSoftVersion()' ==9565==

On Thu, 24 Oct 2024 13:23:56 -0400 Toby Hocking <tdhock5 at gmail.com> wrote: > The patch you are proposing to base R is > https://github.com/Rdatatable/data.table/issues/6566#issuecomment-2428912338 > right? Yes, it's this one, thank you for providing the link. Surprisingly, a very cursory check of 100 packages most downloaded from cloud.r-project.org in the last month

Dear R core developers, One feature from Python that I have been wanting in R is the ability to capture groups in regular expressions using names. Consider the following example in R. > notables <- c(" Ben Franklin and Jefferson Davis","\tMillard Fillmore") > name.rex <- "(?<first>[A-Z][a-z]+) (?<last>[A-Z][a-z]+)" > (parsed <-

On Wed, 8 Jan 2020, I?aki Ucar wrote: > On Wed, 8 Jan 2020 at 19:21, Toby Hocking <tdhock5 at gmail.com> wrote: >> >> Hi R-core, I was wondering if somebody could please add jsslogo.jpg to the >> R sources? (as I reported yesterday in this bug) >> >> https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17687 >> >> R already includes jss.cls which

Hi Hilmar and Ivan, I have used your code examples to write a blog post about this topic, which has figures that show the asymptotic time complexity of the various approaches, https://tdhock.github.io/blog/2023/df-partial-match/ The asymptotic complexity of partial matching appears to be quadratic O(N^2) whereas the other approaches are asymptotically faster: linear O(N) or log-linear O(N log N).

Thanks for the quick response Ivan. readLines with encoding='latin1' works for me (on Ubuntu). However I was more concerned with the inconsistency in results between substr and regexpr. I was expecting that if one of them errors because of an unknown encoding then the other should as well. Even better, if regexpr works, why shouldn't substr work as well? Incidentally the analogous

Dear Toby, Have you tried adding output to the tests with the context() function? Best regards, Thierry Op 4 mei 2015 18:28 schreef "Toby Hocking" <tdhock5 at gmail.com>: I am the author of R package animint which uses testthat for unit tests. This means that there is a single test file (animint/tests/testthat.R) and during R CMD check we will see the following output *