similar to: sibling list element reference during list definition

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 --

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

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

Hello, I use the simplest of examples that somebody can think of in order to generate a matrix of random numbers from within C, calling appropriate R functions. The concrete example is below: --- file pico.c #include <stdio.h> #include <stdlib.h> #include <math.h> #include <R.h> #include <Rmath.h> #define COLM( i, j, m ) ( m*j + i) void pico ( double *y, int n,

Hi Everyone I have a function f which does something using a function g. Function f is in a library and g has a default stub in the library but will be mainly overloaded in a later R script. For example: ########## In a compiled package 'P' ################# g <- function() { cat("Original function g"); } f <- function( newGsource=NULL ) { if(

I have a set of character vectors of uneven length that I have stored in a list. I can easily enough get any column of them using lapply but what I want is to be able to create a matrix of them. Other than some kind of brute force looping approach I have drawn a blank. Would somebody please suggest something? Thanks Example. mylist <- list(aa=c("cat","peach" ),

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:

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

Hi all, I'm trying to use lapply on a list with the following command: out<-lapply(mylist,myfun,par1=p,par2=d) (1) where myfun<-function(x,par1,par1) {.....} (2) now this function is in fact a wrapper for some Fortran code I have written so I think this might be the problem. When I call lapply() as in (1) I get the following message: Error in get(x,

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

Hi All I have a dataframe: myframe<-data.frame(ID=c("first","second"),x=c(1,2),y=c(3,4)) And I have a function myfun: myfun<-function(x,y) x+y I would like to write a function myfun2 that takes myframe and myfun as parameters and returns a list as below: mylist $first [1] 4 $second [2] 6 Could you please help me with this? Doesn't seem like the

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

Hi, I am moving from MATLAB, where one can easily assign a number of output values from a function like this: [x,y] = myfun(a,b) Then variables x and y can be directly used in the caller workspace. I understand that R functions return a single argument, which could be a list. This in a way makes it possible to return multiple values with a single function call, but accessing the list variables

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 }

I have the following contrived code in package format. On Solaris and Mac OS X, code runs just fine. On Windows, it crashes the R environment with the "Send Bug Report" dialog. I tried R 1.8.1 (Win2K) and R 1.9 (WinXP) binaries with the same result. PCs otherwise appear properly configured for creating R packages. Anything blatantly wrong? Suggestions? TIA Relevant files from package