search for: bit64

Dear package maintainers, Dear users of packages `bit`, `bit64`, `ff`, Everyone interested in sustainable sorting algorithms, I submitted updated versions for the upcoming R 4.5.0. The are only minor changes (see the NEWS files) but there is one important change in bit64: ??? o setting options(integer64_semantics="new") ????? gives the better...

Dear package maintainers, Dear users of packages `bit`, `bit64`, `ff`, Everyone interested in sustainable sorting algorithms, I submitted updated versions for the upcoming R 4.5.0. The are only minor changes (see the NEWS files) but there is one important change in bit64: ??? o setting options(integer64_semantics="new") ????? gives the better...

Dear R-Core team, Dear Rcpp team and other package teams, Dear R users, The new package 'bit64' is available on CRAN for beta-testing and code-reviewing. Package 'bit64' provides fast serializable S3 atomic 64bit (signed) integers that can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, charact...

Dear R-Core team, Dear Rcpp team and other package teams, Dear R users, The new package 'bit64' is available on CRAN for beta-testing and code-reviewing. Package 'bit64' provides fast serializable S3 atomic 64bit (signed) integers that can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, charact...

Dear R community, The new version of package 'bit64' - which extends R with fast 64-bit integers - now has fast (single-threaded) implementations of the most important univariate algorithmic operations (those based on hashing and sorting). Package 'bit64' now has methods for 'match', '%in%', 'duplicated', '...

Dear R community, The new version of package 'bit64' - which extends R with fast 64-bit integers - now has fast (single-threaded) implementations of the most important univariate algorithmic operations (those based on hashing and sorting). Package 'bit64' now has methods for 'match', '%in%', 'duplicated', '...

...would keep working indefinitely. *** 2010 SOLUTION*** There were 2 possibilities at the time: a) Using 64-bit integers. b) Using "double precision integers": Solution Finally Chosen at 2010. Reason: In order that not all R packages using compiled code had to be patched extensively. *** BIT64 PACKAGE*** Nowdays, we have 'bit64' Package, which provides serializable S3 atomic 64bit (signed) integers (+-2^63). But this are not a replacement for 32bit integers, as integer64 are: * Not supported for subscripting. * Have different semantics when combined with double, e.g. integer64...

Hi Juan, Comments inline. On Wed, May 29, 2019 at 12:48 PM Juan Telleria Ruiz de Aguirre < jtelleria.rproject at gmail.com> wrote: > Dear R Developers, > > There is an interesting issue related to "reticulate" R package which > discusses how to convert Python's non-32 bit integers to R, which has had > quite an exhaustive discussion: > >

>>>>> Juan Telleria Ruiz de Aguirre >>>>> on Mon, 3 Jun 2019 06:50:17 +0200 writes: > Thank you Martin for giving to know and developing 'Rmpfr' library for > unlimited size integers (GNU C GMP) and arbitrary precision floats (GNU C > MPFR): > https://cran.r-project.org/package=Rmpfr > My question is: In the long term

>>>>> Juan Telleria Ruiz de Aguirre >>>>> on Thu, 30 May 2019 18:46:29 +0200 writes: >Thank you Gabriel for valuable insights on the 64-bit integers topic. >In addition, my statement was wrong, as Python3 seems to have unlimited >(and variable) size integers. .... If you are interested in using unlimited size integers, you could use the

Thank you Martin for giving to know and developing 'Rmpfr' library for unlimited size integers (GNU C GMP) and arbitrary precision floats (GNU C MPFR): https://cran.r-project.org/package=Rmpfr My question is: In the long term (For R3.7.0 or R3.8.0): Does it have sense that CMP substitutes INTSXP, and MPFR substitutes REALSXP code? With this we would achieve that an integer is always an

Dear R Developers, There is an interesting issue related to "reticulate" R package which discusses how to convert Python's non-32 bit integers to R, which has had quite an exhaustive discussion: https://github.com/rstudio/reticulate/issues/323 Python seems to handle integers differently from R, and is dependant on the system arquitecture: On 32 bit systems uses 32-bit integers,

...uble, so it requires adding an S3 class and overriding every generic function with a custom method. Not all functions are generic, and internal C code will not know about the special class, so this has the danger of code silently interpreting the data incorrectly. This is the approach taken by the bit64 package (and, I believe, the int64 package, but since that's been archived it's not worth considering. Hadley On Fri, Jan 20, 2017 at 9:19 AM, Gabriel Becker <gmbecker at ucdavis.edu> wrote: > I am not on R-core, so cannot speak to future plans to internally support > int8 (th...

Thank you Gabriel for valuable insights on the 64-bit integers topic. In addition, my statement was wrong, as Python3 seems to have unlimited (and variable) size integers. Here is related CPython Code: https://github.com/python/cpython/blob/master/Objects/longobject.c Division between Int-32 and Int-64 seems to only happen in Python2. Best, Juan El mi?rcoles, 29 de mayo de 2019, Gabriel

Well I definitely cannot use them as numeric because join is the main reason of those identifiers. About int64 and bit64 packages, it's not a solution, because I am releasing a dataset for external users. I cannot ask them to install a package in order to exploit them. I have to be very carefull when releasing the data. If a user just use read.csv functions, they by default cast the identifiers as numeric. $ mo...

...ngs. Factors are fast for joins. > > ~G > > On Fri, Jan 20, 2017 at 9:47 AM, Nicolas Paris <nicolas.paris at aphp.fr> wrote: > > Well I definitely cannot use them as numeric because join is the main > reason of those identifiers. > > About int64 and bit64 packages, it's not a solution, because I am > releasing a dataset for external users. I cannot ask them to install a > package in order to exploit them. > > I have to be very carefull when releasing the data. If a user just use > read.csv functions, they by defau...

...s g729 but we do not have any g729 licenses on the box because we are doing pass-through so I figure the cpu usage should not be a problem and some sort of bandwidth issue would be hit first. Hardware stats: AMD Athlon(tm) 64 Processor 3000+ 512M of RAM 100Mb/s full duplex switched ethernet Linux bit64.foo.com 2.6.9-1.667 #1 Tue Nov 2 14:50:10 EST 2004 x86_64 x86_64 x86_64 GNU/Linux Software: Asterisk CVS-HEAD-11/26/04-12:38:01 built by root@bit64.foo.com on a x86_64 running Linux asterisk-oh323-0.7.0 The problem: If we point 24 voice channels of traffic at the box we see 5% cpu utilization an...

Hello r users, I have to deal with int8 data with R. AFAIK R does only handle int4 with `as.integer` function [1]. I wonder: 1. what is the better approach to handle int8 ? `as.character` ? `as.numeric` ? 2. is there any plan to handle int8 in the future ? As you might know, int4 is to small to deal with earth population right now. Thanks for you ideas, int8 eg: human_id

...instlara ese paquete? Un saludo Jesús ________________________________ De: Carlos Ortega <cof en qualityexcellence.es> Enviado: viernes, 6 de octubre de 2017 14:51 Para: Jesús Para Fernández Cc: r-help-es en r-project.org Asunto: Re: [R-es] Importando mal los datos Instala el paquete "bit64".... Saludos, Carlos Ortega www.qualityexcellence.es<http://www.qualityexcellence.es> El 6 de octubre de 2017, 14:43, Jesús Para Fernández <j.para.fernandez en hotmail.com<mailto:j.para.fernandez en hotmail.com>> escribió: Buenas chicos, Estoy intentando importar el csv qu...

Buenas chicos, Estoy intentando importar el csv que adjunto y que tiene la siguietne forma: "a";"b" 11092740;0 8978056137;0 Usando la funcion fread. Necesito usar la función fread por velocidad (lo que envio es un ejemplo simplificado pero que replica el error). El problema es que al importar los datos, usando: datos<-fread(datos.csv,sep=";") el campo a no lo