similar to: When to use LazyLoad, LazyData and ZipData?

I added a new data file, NLSY.RData, to a package that uses LazyData: Yes It passed R CRAN check and R CMD install worked w/o significant complaints. * installing to library 'C:/R/R-2.15.2/library' * installing *source* package 'heplots' ... ** R ** data ** moving datasets to lazyload DB ** demo ** inst ** preparing package for lazy loading Warning: package 'nnet' was

Hi, On Windows, package files in the inst/ subdir are installed after the lazyload creation. This differs from Linux where inst/ is installed _before_ lazyload creation. Since packages may need data in inst, I think the order on Windows should be changed. Perhaps like this: diff --git a/src/gnuwin32/MakePkg b/src/gnuwin32/MakePkg index 57af321..868e8f1 100644 --- a/src/gnuwin32/MakePkg +++

I'm writing a couple of related functions, and I'd like to generate a (single) .R file (containing the function definitions), and separate .Rd files (documenting each function). Would this be possible with Sweave/noewb? Has anyone tried something along this idea? -- Regards, Bj?rn-Helge Mevik

On Mon, Aug 24, 2015 at 11:29 AM, Bj?rn-Helge Mevik <b.h.mevik at usit.uio.no> wrote: > arnaud gaboury <arnaud.gaboury at gmail.com> writes: > >> - Intel MKL: this is part of Intel Parallel Studio and is a paid >> software. Now, there is the MKL package distributed by >> Revolutionanalytics, but I am not certain how this can be distributed >> for free. Is

Dear all, apply(X, MARGIN, FUN, ...) returns an array of dimension c(n, dim(X)[MARGIN]) when FUN returns a vector of length n > 1. Matrices and arrays are also vectors, so if FUN returns a matrix or an array, apply returns an array of dimension c(n, dim(X)[MARGIN]) as above. This is in accordance with the description of apply in the Blue Book, and also how Splus works (at least v6.0). I am

Hi All, would appreciate an answer on this if you have a moment; Is there a function (before I try and write it !) that allows the input of a covariance or correlation matrix to calculate PCA, rather than the actual data as in princomp() Regards Glenn [[alternative HTML version deleted]]

make check of R-alpha_2006-04-08_r37675 fails on Debian GNU/Linux 3.1 running on an Intel P4 computer. > version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status

I haven't been able to connect to http://bugs.r-project.org the last few days. Is there a problem with the site (or am I having a problem :-) ? -- Bj??rn-Helge Mevik

Duncan Murdoch <murdoch.duncan at gmail.com> writes: > users of other languages may want to have messages and variable names > in their native language, and ASCII might not be enough for that. Allowing for messages in non-ASCII encodings would probably be a good idea, but I think allowing non-ASCII variable names is dangerous. -- Regards, Bj?rn-Helge Mevik

I want to build R optimized, with either MKL, OpenBLAS or ATLAS. My OS: Fedora 22 Hardware: CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian CPU(s): 8 Thread(s) per core: 2 Vendor ID: GenuineIntel Model name: Intel(R) Core(TM) i7-2600K CPU @ 3.40GHz I am a little confused when it comes to choose a method and would like to hear your experiences. If I am right, I have 3 possibilities: -

Dear developeRs, I use Red Hat Enterprise Linux WS release 4 (Nahant Update 2) on an x86_64 machine (two Intel P4 CPUs with 64 bit support), and R-beta_2005-12-12_r36712.tar.gz. If I run configure without any options, it does not list tcltk among the supported interfaces: ./configure [...] R is now configured for x86_64-unknown-linux-gnu Source directory: . Installation directory:

Getting a very strange error with a new install of R from source on x86; make[3]: Leaving directory `/tmp/R.INSTALL.r20887/cluster/src' ** R ** data ** moving datasets to lazyload DB Error in factor(c(1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1), : invalid labels; length 2 should be 1 or 1 Execution halted ERROR: lazydata failed for package 'cluster' ** Removing

Hi, I think I've found a bug in R CMD INSTALL. When it tries to parse a DESCRIPTION file with an invalid LazyData field, it errors out while trying to print the correct error message: > R CMD INSTALL . * installing to library ?/home/example/R/x86_64-pc-linux-gnu-library/3.4? * installing *source* package ?samplepackage? ... ** data Error in errmsg("invalid value of ", field,

Full_Name: Bj?rn-Helge Mevik Version: 2.1.0 OS: GNU/Debian 3.0 Linux Submission from: (NULL) (80.111.104.162) In Appendix B R coding standards of the Writing R Extensions manual, Emacs/ESS users are encouraged to use (add-hook 'ess-mode-hook (lambda () (ess-set-style 'C++) ;; [snip] (add-hook 'local-write-file-hooks

Dear developeRs, As of icc 10, the -c99 option is deprecated, and generates a lot of warnings when compiling R or R packages. If you use CC="icc -std=c99" instead of just CC="icc", R's configure will not add the -c99 option, and the code seems to compile and run just fine. (Please don't hesitate to let me know if this is a bad idea. :-) -- Regards, Bj?rn-Helge

Hello, I have a data set with 15 variables (first one is the response) and 1200 observations. Now I use pls package to do the plsr as below. trainSet = as.data.frame(scale(trainSet, center = T, scale = T)) trainSet.plsr = mvr(formula, ncomp = 14, data = trainSet, method = "kernelpls", model = TRUE, x = TRUE, y = TRUE) from the model, I wish to know the

Hi, In the DESCRIPTION file the ByteCompile and LazyLoading arguments appear to accept any value. >From the manual the field should be a "logical field". However, authors interpret this in a variety of ways: unique(tools::CRAN_package_db()$ByteCompile) # [1] NA "TRUE" "yes" "true" "Yes" "no" #

In DESCRIPTION if I set LazyLoad to 'yes' will data.table (for example) then be byte compiled for users who install the binary package from CRAN on Windows? This question is based on reading section 1.2 of this document : http://www.divms.uiowa.edu/~luke/R/compiler/compiler.pdf I've searched r-devel and Stack Overflow history and have found questions and answers relating to R CMD

Hi the list I have package foo0 with a big dataset 'myData'. In DESCRIPTION, if I use 'LazyData: no', then I get: - when I open a R session : memory used=20 908 - when I attach 'library(foo0)' : memory used=24364 - then I load the set 'data(myData)' : memory used=39 668 If I use LazyData: yes', then I get - when I open a R session : memory used=20 908

As far as I can tell, there are no facilities in the "base" R for image analysis. Is there any extension or package for R that implements image analysis? I'm thinking of features such as o Reading and writing image files, o displaying indexed or "true color" images, o resizing, cropping, etc, of images, o filters for manipulating images (smoothing, edge detection, etc) o