[Rd] stats, pics etc on CRAN
Does anyone have some nice ways of showing what's on CRAN? A time-series of the number of packages? A clustered graph of packages by keyword? I'm just after a more impressive way of saying there's 2600 packages on CRAN than saying that. Counts of lines of R and C/Fortran code would be interesting... The CRANtastic tag cloud is quite handy... Anything else? Barry __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] stats, pics etc on CRAN
On Mon, Nov 1, 2010 at 3:20 PM, Barry Rowlingson b.rowling...@lancaster.ac.uk wrote: Does anyone have some nice ways of showing what's on CRAN? A time-series of the number of packages? A clustered graph of packages by keyword? I'm just after a more impressive way of saying there's 2600 packages on CRAN than saying that. Counts of lines of R and C/Fortran code would be interesting... The CRANtastic tag cloud is quite handy... Anything else? There was an article with a graph here: http://journal.r-project.org/archive/2009-2/RJournal_2009-2_Fox.pdf -- Statistics Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] BLAS benchmarks on R 2.12.0
On Sun, Oct 31, 2010 at 12:41:24PM -0400, Michael Spiegel wrote: 1) Compile the reference BLAS implementation with unsafe optimizations and include it as a part of the OpenMx library. If BLAS speed is important to you, why are you even trying to use the slow reference BLAS library at all, rather than one of the faster optimized BLAS libraries (Atlas, Goto, AMD, Intel, etc.)? -- Andrew Piskorski a...@piskorski.com http://www.piskorski.com/ __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] BLAS benchmarks on R 2.12.0
Hi Andrew, In the majority of use cases of our package, we end up doing lots and lots of matrix operations on small matrices, as opposed to matrix operations on large matrices. The optimized BLAS libraries are usually optimized for large matrices. The reference implementation is faster than either veclib, Atlas, or the Goto BLAS implementations, I've tested all of them on our performance test suite. --Michael On Mon, Nov 1, 2010 at 6:07 PM, Andrew Piskorski a...@piskorski.com wrote: On Sun, Oct 31, 2010 at 12:41:24PM -0400, Michael Spiegel wrote: 1) Compile the reference BLAS implementation with unsafe optimizations and include it as a part of the OpenMx library. If BLAS speed is important to you, why are you even trying to use the slow reference BLAS library at all, rather than one of the faster optimized BLAS libraries (Atlas, Goto, AMD, Intel, etc.)? -- Andrew Piskorski a...@piskorski.com http://www.piskorski.com/ __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
[Rd] can not built a package
Dear all, I tried to build a package from source, and ran into a problem. R CMD build RQDA * checking for file 'RQDA/DESCRIPTION' ... OK * preparing 'RQDA': * checking DESCRIPTION meta-information ... OK ERROR copying to build directory failed I searched and found this http://r.789695.n4.nabble.com/tar-problem-when-using-R-CMD-build-on-Windows-td2734636.html SET TAR=tar --no-same-owner R CMD build RQDA the same error. The R sessionInfo is: sessionInfo() R version 2.12.0 Patched (2010-10-28 r53459) Platform: i386-pc-mingw32/i386 (32-bit) locale: [1] LC_COLLATE=Chinese (Simplified)_People's Republic of China.936 [2] LC_CTYPE=Chinese (Simplified)_People's Republic of China.936 [3] LC_MONETARY=Chinese (Simplified)_People's Republic of China.936 [4] LC_NUMERIC=C [5] LC_TIME=Chinese (Simplified)_People's Republic of China.936 attached base packages: [1] stats graphics grDevices utils datasets methods base -- Wincent Ronggui HUANG (Ph.D.) City University of Hong Kong http://asrr.r-forge.r-project.org/rghuang.html __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
