similar to: How do I reliably and efficiently hash a function?

In addition to what Charles wrote, you can also use 'local' if you don't want a function that creates another function. > f <- local({info <- 10; function(x) x + info}) > f(3) [1] 13 best, Mark Op vr 11 dec. 2015 om 03:27 schreef Charles C. Berry <ccberry at ucsd.edu>: > On Thu, 10 Dec 2015, Konrad Rudolph wrote: > > > I?ve got the following scenario:

On Thu, Dec 10, 2015 at 5:49 PM, Konrad Rudolph <konrad.rudolph+r-devel at gmail.com> wrote: > I?ve got the following scenario: I need to store information about an > R function, and retrieve it at a later point. In other programming > languages I?d implement this using a dictionary with the functions as > keys. In R, I?d usually use `attr(f, 'some-name')`. However, for

On Thu, 10 Dec 2015, Konrad Rudolph wrote: > I?ve got the following scenario: I need to store information about an > R function, and retrieve it at a later point. In other programming > languages I?d implement this using a dictionary with the functions as > keys. In R, I?d usually use `attr(f, 'some-name')`. However, for my > purposes I do not want to use `attr` because the

Dear list, I have two functions created in the same environment, fun1 and fun2. fun2 is called by fun1, but fun2 should use an object which is created in fun1 fun1 <- function(x) { ifelse(somecondition, bb <- "o", bb <- "*") ## mymatrix is created, then myresult <- apply(mymatrix, 1, fun2) } fun2 <- function(idx) { if (bb == "o) { #

Hi R users: I'm trying to make a function where two of the parameters are functions, but I don't know how to put each set of parameters for each function. What am I missing? I try this code: f2<-function(n=2,nsim=100,fun1=rnorm,par1=list(),fun2=rnorm,par2=list()){ force(fun1) force(fun2) force(n) p1<-unlist(par1) p2<-unlist(par2) force(p1) force(p2)

Thanks. Yes. Your approach can identify: Glaxy ace S 5830 and S 5830 Glaxy ace But you can not identify using same program: Iphone 4S 16 G Iphone 4S 16G How should I solve both in same time. Kind regards,Tammy [[alternative HTML version deleted]]

Hello I need some help in figuring Bravington’s debugger out. Ok I have 2 functions, fun1 and fun2 saved in a ASCII file say filename is funs. Fun1 has a loop which calls fun2, fun2 has a loop which fails and I need to find out the value of the variables of the fun2 and fun1 loops at the specific iteration that fails. Both fun1 and fun2 loops will iterate thousands of times so line by line debug

Dear list, I know I have seen this discussed before but I haven't been successful in searching for "ellipsis", "dots", "..." in the archives. I would like to filter "..." arguments according to their name, and dispatch them to two sub-functions, say fun1 and fun2. I looked at lm() but it seemed more complicated than I need as it modifies the calling

I'm looking for a way to approximate the "zero-overhead" model of code reuse available in languages like Python, Perl, etc. I've described this idea in more detail, and the motivation for this question in an earlier post to R-help (https://stat.ethz.ch/pipermail/r-help/2016-September/442174.html). (One of the responses I got advised that I post my question here instead.) The

Dear Friends, Let's assume there are three parameters that were passed into fun1. In fun1, we need to modify one para but the remains need to be untouched. And then all parameters were passed into fun2. However, I have failed to achieve it. Please see the following code. ########################################## fun1 <-function(x, y, z=10) {x+y+z;} fun2 <-function(aa, ...) {

Dear list! ? I have question of?'correct function formation'. Which function (fun1 or fun2; see below) is written more correctly? Using ''structure'' as output or creating empty ''data.frame'' and then transform it as output? (fun1 and fun1 is just for illustration). ? Thanks a lot, OV ? code: input <- data.frame(x1 = rnorm(20), x2 = rnorm(20), x3 =

Dear list!   I would like to write a function to transform matrix, which is input argument of a written function. It is easy with new matrix (see below), but my idea is to transform input argument (matrix) of function without any additional matrixes. Here is an example: fun1 <- function(xy) { xy <- cbind(xy[,1], xy[,2], xy[,1] + xy[,2]) return(xy) }   df1 <- matrix(c(1,2,3,1,2,3), ncol =

Hello, I'm building a package. My code is stored in foo.R. This code has two functions FUN1 and FUN2. FUN1 calls FUN2. FUN1 is listed in export() under the package NAMESPACE but NOT FUN2. After building the package when I call FUN1 is giving me an error that cannot find FUN2. I solved this by adding FUN2 in the export() NAMESPACE. However, what is puzzling me is that I have other examples

I'm not sure if this is what you want, but simply add ... to the list of arguments for fun1 and fun2 would eliminate the error. Andy From: Hans-Joerg Bibiko > > Dear all, > > I wrote some functions using the special argument '...'. OK, it works. > > But if I call such a function which also called such a > function, then I get an error message about unused

> On Feb 24, 2015, at 10:50 AM, <luke-tierney at uiowa.edu> wrote: > > The documentation is not specific enough on the indented semantics in > this situation to consider this a bug. The original R-level > implementation of lapply was > > lapply <- function(X, FUN, ...) { > FUN <- match.fun(FUN) > if (!is.list(X)) > X <-

Full_Name: Yi-Xiong Zhou Version: 1.5.1 OS: win2000pro Submission from: (NULL) (64.169.249.42) Update() can not find objects when it is used in a function, which is in turn being called by another function. Here is a R script to show the problem: ######## begin of the test script ########## fun1 <- function() { x <- matrix(rnorm(500), 20,25) y <- rnorm(20) oo <- lm(y~x)

Hello! Maybe "frame" is not the right term in this context. I explain my problem by example code: fun2 <- function(objName, add) { ## the object "objName" should be increased by "add", ## but the evaluation should be done in the calling function (here: fun1) ## ...... what's the right code?? } fun1 <- function() { x <- 1 fun2("x",

Hi R-users, I have a function (myfun) that I want to apply to the rows of a matrix. Basically, "myfun" takes the values from the matrix ("exp.des"), which represent the different combinations of my experimental design, and pass them as arguments to some other functions (fun1 and fun2). As I want to replicate the results of fun1 and fun2 a certain number of time (e.g. 5), I

Dear R-users, i have to integrate the following function `fun1` <- function (a, l1, l2) { exp(log(l1) * (a - 1) - l2 * lgamma(a)) } but if l1 is large, i get the "non-finite function value" error, so my idea is to rescale with exp(-l1) `fun2` <- function (a, l1, l2) { exp(log(l1) * (a - 1) - l2 * lgamma(a) - l1) } but it seems this doesn't solve the problem, when

I'm noticing some interesting behavior in `match.call` in some corner-ish cases that arise when you try to use `match.call` to match a "grandparent" function and there are dots involved: fun0 <- function(a, ...) fun1(...) fun1 <- function(b, ...) fun2() fun2 <- function() match.call( fun1, sys.call(sys.parent()), expand.dots=FALSE,