similar to: Converting non-32-bit integers from python to R to use bit64: reticulate

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

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 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

>>>>> 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

Hola Diego, Prueba a hacer otra cosa. - Abre una consola y activa ese environment que has creado (r-reticulate) - Y una vez activado escribe "python". Entrarás a la consola de "python". - Ahí, escribe "import transformers" - Si no te devuelve error, es que en el entorno está bien instalado esa librería y por tanto el problema es de acceso desde

Estimados Una pregunta, ¿Que posibilidad hay que esté instalado todo correctamente, pero algo cambie en entorno de python, el cual al ser buscado por R esté dando problemas? Hace años que no utilizo macOS, pero se me ocurre que un programa coloque en entorno adecuado para él, pero al mismo tiempo este toque al entorno requerido por R. Javier Rubén Marcuzzi El dom., 2 ago. 2020 a las 15:59,

Thank you Frederick for your comments: They are really well justified. > I think a "forum" or bulletin board system would be a detraction from the project and a distraction for the project leaders. Users have Stack Exchange - it's better than any forum we could create, and it > takes care of itself. An excellent idea would be to add in the R Project Webpage a link to RSeek,

Estimados compañeros: Estoy interesado en el NLP, así que, al hallar el post State-of-the-art NLP models from R <https://blogs.rstudio.com/ai/posts/2020-07-30-state-of-the-art-nlp-models-from-r/>, gracias a Carlos Ortega, me puse con ilusión a leerlo. Sin embargo, tengo problemas con lo más básico, la instalación del paquete *transformers*. No puedo

Dear all, I have written a little R program to convert images. See below. Within the loop over j (the filenames) memory consumption grows constantly. rm( ... ) inside the loop did not help. Memory does not grow if I remove the writeBin statements between the two #-------- marks. But obviously this is not solution I want... Thanks for any advice. Manfred Baumstark P.S. As I'm new to R:

Estimados Recuerdo que hace unos años en esta lista con uno de los Carlos se había creado un hilo sobre R y python, hoy leo una noticia, por lo menos para mí, que podría entrar en esa situación entre lo mejor de dos alternativas. Lógicamente, es nuevo para mí, no puedo opinar nada más que compartir la información, probar, usar, y cada uno puede utilizar o rechazar la herramienta. Miren

Full_Name: Prokaj Vilmos Version: R 2-4-0 OS: Windows Submission from: (NULL) (193.224.79.8) PackBits(rbinom(32,1,0.5)==1,"integer") does not work. z<-packBits(rbinom(32,1,.5)==1,"integer") Error in packBits(x, type) : argument 'x' must be raw, integer or logical Taking a closer look at the C code main/character.c do_packBits rutin one can find the following

Full_Name: Ed Borasky Version: 1.8.1 OS: Windows XP Professional Submission from: (NULL) (208.252.96.195) R 1.8.1 seems to be running into a memory allocation problem in the "aggregate" function. I have a rather large dataset (14 columns by 223,000 rows -- almost 40 megabytes) and a script that performs some processing on it. The system is a 768 MB Pentium 4. Here's the console

Dear R List, I encountered a serious problem regarding the registration of ".C" when following the documentation "Writing R Extensions" that leads to a segmentation fault (tested on windows and mac os x). The registration mechanism for ".C" routines via R_registerRoutines and the R_CMethodDef structure has been enhanced recently with the addition of two fields, one

[some de-capitalization of *SXP done manually by mailing list maintainer ; the originally was caught as potential spam. MM] I have a little R program that crashes with the message xmalloc: out of virtual memory The code has a repeat{} loop that watches the sizes of some files. When there's an increase it updates things by reading the last 65 lines of each file, doing some

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', 'unique', 'table',

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', 'unique', 'table',

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,

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,

I've looked at how to speed up the transpose function in R (ie, t(X)). The existing code does the work with loops like the following: for (i = 0; i < len; i++) REAL(r)[i] = REAL(a)[(i / ncol) + (i % ncol) * nrow]; It seems a bit optimistic to expect a compiler to produce good code from this. I've re-written these loops as follows: for (i = 0, j = 0; i<len; i +=