similar to: Disable LazyLoading mechanism completely

Hola! I got past the problems I asked about two days ago, thanks. No I am updating CRAN package asypow (the daily package check on CRAN gave warnings due to .Rd problems, fixed). Now it PASSED Rcmd check (WindowsXP home edition, rw2000dev, on a new toshiba laptop, if that matters.) but then Rcmd build --binary gives problems: . . . preparing package asypow for lazy loading Error in

Can the value of a list element be referenced from a sibling list element during list creation without the use of a temporary variable? The following doesn't work but it's the general idea. > list(value = 2, plusplus = $value+1) such that the following would be the output from str() List of 2 $ value : num 2 $ plusplus: num 3

How would one go about getting sprintf to use the values of a vector without having to specify each argument individually? > v <- c(1, 2, -1.197114, 0.1596687) > iv <- c(3, 1, 2, 4) > sprintf("%9.2f\t%d\t%d\t%8.3f", v[3], v[1], v[2], v[4]) [1] " -1.20\t1\t2\t 0.160" Essentially, desired effect would be something like: >

What's the best way to simulate Recall for parent function? Consider this one-time recursive code: alwaysEven <- function(x) { handleOdd <- function(x) { alwaysEven(x-1) # use Recall-like here } return(if (x %% 2) handleOdd(x) else x) } any2even <- alwaysEven rm(alwaysEven) any2even(3) ---------------------------------------------------------- SIGSIG --

Was looking at what was output for <pkgname>-package.Rd and wondered if any there was any means (via macro, etc) to merge some of the same information with a template for my package manpage? As much (all?) of the generated information was already provided in the DESCRIPTION, I'd prefer not to have to update the information in multiple places. I'm thinking here that I could provide a

I have the following: > a <- matrix(1:10, nrow = 2, byrow = TRUE) > b <- array(as.integer(0), c(7, 5)) > idx <- list() > length(idx) <- 2 > dim(idx) <- c(1, 2) > idx[[1]] <- as.integer(1:2) > idx[[2]] <- as.integer(1:5) I can do the following, which works if 'b' is a matrix. > b[idx[[1]], idx[[2]]] <- a > b [,1] [,2] [,3] [,4] [,5]

I have some code where the primary dispatching is on other parameters so I'd like not to have to create a set of functions for "matrix" and another duplicate set for "array". But the class union technique isn't working as implemented below and I don't have my Green book with me. How do I fix my infinite recursion problem?

On Mon, 6 Feb 2006 18:12, Simon Urbanek wrote: > On Feb 6, 2006, at 5:24 PM, Paul Roebuck wrote: > >> Tried on R-Sig-Mac with no responses, but I need some kind >> of answer. >> [...] >> Does the following work on your system? > > Interesting, no, it doesn't either. For png and pdf I use > Quartz + quartz.save (it produces much nicer results) so > I

Hi all, Bioconductor has several metaData packages that contain quite large data sets. In the past, these data were simply held in the /data directory of the package as .rda files and load()ed as needed. Converting to using lazy data loading may have memory and performance advantages, but for the larger metaData packages the installation is painfully slow (it has taken > 30 min to install a

Is there a means to split a vector into its individual elements without going the brute-force route for arguments to a predefined function call? offred.rgb <- c(1, 0, 0) * 0.60; ## Brute force style offred.col <- rgb(offred.rgb[1], offred.rgb[2], offred.rgb[3], names = "offred") ## Desired style

I recently encountered this and was wondering if someone could explain what happened. Basis of question involves what the difference between the calls makes as the end result is the same: > identical(matrix(1:8, nrow = 1), array(1:8, c(1, 8))) TRUE If I run the code below as shown, I get the following: > foo(1:8, 4) foo (vector, numeric) val = 4 foo (matrix, ANY) val = 500 foo

Anyone aware of tools available that can provide complexity metrics and/or code coverage analysis for R source? ---------------------------------------------------------- SIGSIG -- signature too long (core dumped)

Dear developeRs, I've searched the documentation, FAQ, and mailing lists, but haven't found the answer(*) to the following: When should one specify LazyLoad, LazyData, and ZipData? And what is the default if they are left unspecified? (*)Except that 1) If the package you are writing uses the methods package, specify LazyLoad: yes, and 2) The optional ZipData field controls whether the

Under Details section for as.Date: as.Date will accept numeric data (the number of days since an epoch), but only is origin is supplied. ^^ should be "if" R version 2.7.0 Patched (2008-06-04 r45830) ---------------------------------------------------------- SIGSIG -- signature too long (core dumped)

What a delicious example! (I'm taking the liberty of sharing it with r-devel, since it raises some good issues.) You have two questions, presumably: 1 - how could the order of the setMethod calls make a difference in the results? 2 - what's causing the infinite loop & how could it be avoided, reliably? Second question first. The danger sign is the "vector" method:

On Sun, 11 Jul 2004, Gabor Grothendieck wrote: > search.path <- > function(fn, > paths = strsplit(Sys.getenv("PATH"), split = ";")[[1]], > fsep = "\\") { > for(d in paths) { > f <- file.path(d, fn, fsep = fsep) > if (file.exists(f)) > return(f) > } > return(NULL) > } >

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 +++

Wish to install a local source package on Un*x platform from within R. Same thing as I can accomplish from cmdline as $ export R_LIBS=~/R/library $ cd /path/to/pkg $ R CMD INSTALL -l $R_LIBS <pkgname> So, how do you go about this anyway? And isn't this a bug in 'install.packages'? ------- $ R R : Copyright 2004, The R Foundation for Statistical Computing Version 1.9.0

I'm translating some Matlab code and need some help figuring out how to change this call into an S4 generic method. In matlab, there's a function called 'repmat' with three calling sequences (all I have to deal with anyway): 1) B = repmat(A, m, n) 2) B = repmat(A, [m n]) 3) B = repmat(A, n) In all cases, A is the fill value, m is number of rows, and n is number of

Is there a canonical means to apply a function over multiple arrays simultaneously? For example, if I wanted to plot each line with a different color? Or is a for loop conversion my best option? x <- seq(0, 8, by = 2) y <- matrix(1:15, nrow = 5, byrow = TRUE) my.colors <- heat.colors(3) drawLines <- function(row) { lines(x, row) # want corresponding 'my.colors' here }