search for: crlmm

Hello, My problem is that I hit the hard-coded MAX_NUM_DLLS (100) limit of the number of loaded DLLs. I have a number of custom packages which interface and integrate a lot of CRAN and Bioconductor packages. For example, on my installation: Rscript -e 'library(crlmm);print(length(getLoadedDLLs()))' gives 28 loaded DLLs. I am currently trying to work-around that by putting external packages in Suggests: instead of Imports:, and lazy-load them, but still I am wondering if that threshold value of 100 is still relevant nowadays, or would it be possible to inc...

...er in an exploratory analysis would end up accessing dozens of packages with orthogonal dependencies. This is also the use case with Karl Forner's post https://stat.ethz.ch/pipermail/r-devel/2015-May/071104.html <https://stat.ethz.ch/pipermail/r-devel/2015-May/071104.html> (adding library(crlmm) to the above gets us to 53 DLLs). > >> >>> The real solution of course would be a code improvement that >>> starts with a relatively small number of "DLLinfo" structures >>> (say 32), and then allocates more batches (of size say 32) if >>> n...

On 04/05/2016 08:44, Martin Maechler wrote: >>>>>> Qin Zhu <qinzhu at outlook.com> >>>>>> on Mon, 2 May 2016 16:19:44 -0400 writes: > > > Hi, > > I?m working on a Shiny app for statistical analysis. I ran into this "maximal number of DLLs reached" issue recently because my app requires importing many other packages.

...it is used), it doesn't seem at all improbable that the user in an exploratory analysis would end up accessing dozens of packages with orthogonal dependencies. This is also the use case with Karl Forner's post https://stat.ethz.ch/pipermail/r-devel/2015-May/071104.html (adding library(crlmm) to the above gets us to 53 DLLs). > >> The real solution of course would be a code improvement that >> starts with a relatively small number of "DLLinfo" structures >> (say 32), and then allocates more batches (of size say 32) if >> needed. > > The probl...

...er in an exploratory analysis would end up accessing dozens of packages with orthogonal dependencies. This is also the use case with Karl Forner's post https://stat.ethz.ch/pipermail/r-devel/2015-May/071104.html <https://stat.ethz.ch/pipermail/r-devel/2015-May/071104.html> (adding library(crlmm) to the above gets us to 53 DLLs). >> >>> >>>> The real solution of course would be a code improvement that >>>> starts with a relatively small number of "DLLinfo" structures >>>> (say 32), and then allocates more ba...