similar to: apply() and unary operators

Hello List How do I turn R> simple.example.alphabetic [,1] [,2] [,3] [1,] "a" "b" "c" [2,] "d" "e" "f" [3,] "g" "h" "i" into R> simple.example.numeric [,1] [,2] [,3] [1,] 1 2 3 [2,] 4 5 6 [3,] 7 8 9 [ie "a" becomes 1, ..., "z"

Hello list (thanks for all the help on my data.frame() question, especially to Professor R for a working script...I was pleased to see the solution wasn't obvious!) Anyway, now I'm trying to run R in batch mode, but I'm getting extra output, which I don't want (RedHat 8.3, R-1.7.0): r:~% cat test.R options(echo=FALSE) write(rnorm(4),"") r:~% R CMD BATCH --vanilla

Hi everyone check this out [R-1.7.0]: R> f1 <- function(x){x^2} R> f1 -> f2 R> f2(4) [1] 16 R> R> function(x){x^2} -> f3 function(x){x^2} -> f3 R> f3(4) Error: couldn't find function "f3" Why does right assignment "->" work in the first but not the second case? Can anyone else reproduce this? -- Robin Hankin, Lecturer, School of

Kia Ora everybody. There must be an obvious answer to this, but I can't see it.... I want four square plots in one postscript file. The canonical answer would be: postscript(file="~/f.ps",width=5,height=5) par(pty="s",mfrow=c(2,2)) plot(1:19,xlab="") plot(1:19,xlab="") plot(1:19,xlab="") plot(1:19,xlab="") dev.off() But this

Hi everyone This must be a FAQ but I can't find it anywhere... I want a postscript image of a contour() plot, with axes of equal length. Try R> postscript(file="~/f.ps") R> contour(matrix(rnorm(100),10,10)) R> dev.off() This isn't what I want: the plotting region is, as documented, quarter of an inch shy of the paper edge and the axes appear to be different lengths.

Hello everybody. Does anyone else find the last test in the following sequence odd? Can anyone else reproduce it or is it just me? > binom.test(100,200,0.13)$p.value [1] 2.357325e-36 > binom.test(100,200,0.013)$p.value [1] 6.146546e-131 > binom.test(100,200,0.0013)$p.value [1] 1.973702e-230 > binom.test(100,200,0.00013)$p.value [1] 0.9743334 (R 1.5.1, Linux RedHat 7.1) --

Hi everyone another documented feature that was a bit unexpected for me: R> x <- 19 R> f <- function(t){t+x} R> f(100) [1] 119 --as expected: x is visible from within f() ..but... R> g <- function(a){x <- 1e99 ; return(f(a))} R> g(4) [1] 23 --the "x" that is visible from within g() is just 19, which is not the one I expected it to find. R> rm(x)

Hi I recently found a bug that was isomorphic to the following: ll1 <- 2 increment <- function(x) { l11 <- 1 return(x+ll1) #bug here } Of course, R is obeying the scoping rules just fine, but I'm evidently not setting the do.what.I.mean.not.what.I.say variable correctly. Now, how do I avoid making this type of error? ... and what is the best tool for tracking it down? --

Hello everyone. If I do f <- function(n){max(rnorm(n))} plot(sapply(rep(5000,4000),f)) #[this takes my PC about 30 seconds] then I get something quite unexpected: gaps in the distribution. For me, the most noticable one is at about 3.6. Do others get this? Is it an optical illusion? It can't be right, can it? Or maybe I just don't understand the good ol' Gaussian very

Hello everybody I have a generic problem which the following toy function illustrates: f <- function(n) { if(abs(n) < pi) { return(TRUE) } else { return(FALSE) } } I want it to return TRUE if abs(n)<pi and FALSE otherwise. f() is fine as far as it goes, but does not deal well with NA or NaN or NULL (I want these to signal some problem with the

Hello everybody. I have a question that has stumped me and the usual "apply" tricks don't seem to work. I run a course where each student's performance is marked by one or more assessors. I have a data frame containing students' names, assessors' names and their marks, arranged as follows: ID student assessor Q1A Q1B Q1C Q2A Q2B Q3 1 2152833

Hi everyone thanks for the replies. The issue was NOT a font problem; I deliberately chose ll1 and l11 as examples of easily confused variable names (evidently these were too easily confused ;-). The code snippet was written as intended, and increment() contained a deliberate, highlighted, bug. I was asking for guidance on avoiding/finding this sort of coding error. That was why I wrote

Robin, the initial output from apply() is always in the form you have below, but if it can be 'simplified' into a structure like the matrix, it does so. The same thing happens with sapply(). If you want to produce a nice matrix as the out put you have to ensure that the simplification is possible. Here is one way. > apply(x2, 2, function(x, v) table(factor(x, levels=v)),

Dear Helplist I have a dataframe that holds the Southern Oscillation Index over the last few years: R> soi[1:3,] Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1 1993 -9 -10 -12 -24 -9 -18 -11 -18 -9 -15 -1 0 2 1994 -2 -1 -14 -26 -13 -12 -18 -20 -19 -16 -9 -15 3 1995 -4 -5 2 -19 -9 -3 4 -1 3 -2 0 -8 QUESTION: how do I coerce reshape() into giving me this:

Hello everybody. I found out the other day something quite astonishing (which I guess is not astonishing at all to those in the know): in d-dimensional space, determining whether a given point is inside the convex hull of a set of n points is elegantly and quickly solvable using linear programming. If the columns of matrix "ff" are the coordinates of the set of points, then in d=2

Hello everybody. I have a dozen or so vectors (of different lengths) which I want to coalesce into a dataframe, as in the following toy example. R> foo <- c(1,2,3) R> bar <- c(7,8) R> data.frame(name =c(rep("foo",length(foo)),rep("bar",length(bar))), value=c(foo,bar)) name value 1 foo 1 2 foo 2 3 foo 3 4 bar 7 5 bar

Dear R-xperts I have just written a little hypergeometric function, included below [the hypergeometric function crops up when solving a common type of ODE]. It works fine on single values of the primary argument z, but vectorizing it is getting confusing. The best I have come up with so far just tests for z being longer than 1 and if so, uses sapply() recursively. This is fine, except that it

Dear R experts I work in computational fluid dynamics in 2D: I have a 200-by-200 array of fluid properties such as density and velocity and these evolve in time (the precise equations depend on the problem). Up to now, I've been using Fortran and the code is very very messy. It works, but a professional programmer friend of mine saw the source code once, and had to be strapped down for his

Dear R community A few weeks ago, I uploaded a small text file called R-and-octave.txt to the contributed docs section of CRAN. This file details octave/matlab commands and their (near) equivalents in R (Matlab is a widely-used high-level graphics/mathematics tool and octave a free clone). Someone has just pointed out to me that I never announced its existence to anyone, hence this email (I

Dear List the other day, I had my yearly staff interview with my Head of Department. Under my list of publications, I included a document which I wrote (R-and-octave.txt) that ended up in the "contributed docs" section of CRAN. Unfortunately, neither my HoD nor the personnel person were terribly impressed with it, even though its preparation time was commensurate with many of my (co