search for: superassignments

Why should it make an exception for cases where the about-to-be-assigned-to name is present in the global environment? I think it should warn or give an error if the altered variable is in any environment on the search list. -Bill On Sun, Mar 19, 2023 at 10:54?AM Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > I think that should be the default behaviour. It's pretty late to

I think that should be the default behaviour. It's pretty late to get that into R 4.3.0, but I think your proposal (with check.superassignment = FALSE being the default) could make it in, and 4.4.0 could change the default to TRUE. Duncan On 19/03/2023 12:08 p.m., Henrik Bengtsson wrote: > I'd like to be able to prevent the <<- assignment operator ("super >

I'd like to be able to prevent the <<- assignment operator ("super assignment") from assigning to the global environment unless the variable already exists and is not locked. If it does not exist or is locked, I'd like an error to be produced. This would allow me to evaluate expressions with this temporarily set to protect against mistakes. For example, I'd like to

I have to say <<- is a core debugging tool when assigning into the global environment. I suppose I could use assign but that would be somewhat annoying. That said I'm still for this change, the vast overwhelming number of times that <<- is in my package code - already rare but it does happen - it would absolutely be a bug (typo most likely) for it to get to the global environment

Hello, I am using the function step.gam() from the 'gam' package (header info from library(help=gam) included below) and have come across some behavior that I cannot understand. In short, I have written a function that 1) creates a dataframe, 2) calls gam() to create a gam object, then 3) calls step.gam() to run stepwise selection on the output from gam(). When I do this, gam()

Dear Helpers, in which way I have to use the assignment-operator evaluating left to right with R 2.0.0? With R 2.0.0 (w2k-installation) the "superassignment" operator '<<-' seems to have a different behaviour compared with R 1.9.1 : > x<<-4 > x [1] 4 > attr(x,'y')<<-5 Error: Object "x" not found > Using earlier

In a clean environment under R-2.1.0 on Linux: > x <- 1:5 > x[3] <<- 9 Error: Object "x" not found Isn't that odd? (Note x <<- 9 works just fine.) Why am I doing this? Because I'm stepping through code that normally lives inside a function, where "<<-" is appropriate. -- David Brahm (brahm at alum.mit.edu)

Hello and thanks in advance for your time. I currently have a simulation running on my cluster with the help of snow that relies on global variables being changes regularly to random values. It uses these values, lets call them x1 x2 and x3, in custom functions for logliklyhood and score that gets used in the standard optim function. To get set in the global table on the different

Hi, Is there a way to find out if a function was called with an output argument? Or to prevent the printing of large amount of data if the function was called without output argument? Thanks YG -------------- next part -------------- An HTML attachment was scrubbed... URL: https://stat.ethz.ch/pipermail/r-help/attachments/20000608/8d7a01ec/attachment.html

I've been reading some code from an example in a blog post ( http://www.maxdama.com/ here ) and I came across an operator that I hadn't seen before. The author used a <<- operator to update a variable, like so: ecov_xy <<- ecov_xy+decay*(x[t]*y[t]-ecov_xy) At first I thought it was a mistake and tried replacing it with the usual <- assignment operator, but I didn't

I'd like to perform return variable assignments like matlab. For example, the following function would return A, B, and c to the script that called it. ================================= function [A,B,c] = simple(m,n) A=[ 3 2; 3 3] B=m c=1:n ================================= I'd like to do similar assignments in R, but I seem to be able to only return one variable. I tried to use a

Hi list! I have a data frame called fix and a list of index vectors called rois: > head(rois, 3) [[1]] [1] 2 1 [[2]] [1] 3 [[3]] [1] 6 7 28 26 27 24 25 The part that's causing the issue is the following line: lapply(rois, function(roi) fix$x[roi] <- 100) So for every index vector I'd like to set the respective entries in the data frame (fix) to 100. I

Martin, I have an objection in principle to anything that has the side-effect of clobbering something in the global environment, even something as innocuous looking as "old.par". I certainly object to putting something like that into a public library, however clever and useful the code might be. It just is not safe. As a quick way round this I suggest the following (R only) solution:

The statement Globals <<- list() in the body of a function in a package was intended to write an empty list to the R workspace to collect results during the computations of the function. A package name space has not been specified. The package appears to function correctly, but during the R CMD check of the package while "checking R code for possible problems ... NOTE", no

Hello, I tried this pseudo-generator style experiment (see below). The "<<-" operator assigns to in the calling environment which would be the environment of "getN". Yet when the function incr is returned, isn't this environment lost? Also the print displays GlobalEnv, yet the globalenv does not have any mention of startgiven. This code was inspired from and old

Is this expected behavior? > z <- 1:5 > z[1] <<- 0 Error in z[1] <<- 0 : object "z" not found The documentation seems to suggest that z will be found in the global environment and modified accordingly. Best, Hsiu-Khuern.

Below is the (really basic) script I am creating to call a function that sets the working directory, determines the number of files it will need to process in that directory, and creates a mask. A "for" loop will eventually be added that will loop through the files (arrays) in that directory performing a baseline/zero correction and apply the mask - that will probably be a later plea

My R code has got too complex to have a non-modular approach. Ive done some coding in other languages before, but I somehow cant figure out R's general rules for global and local variables. I have put a simple code below, if anyone can show me what i need to add to make this work, i would greatly appreciate it! #---------------------------------------- g_Means<-numeric()

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Hello, everybody. I'm putting together some lecture notes and course exercises on R programming. My plan is to pick some R packages, ask students to read through code and see why things work, maybe make some changes. As I look for examples, I'm running up against the problem that packages use coding idioms that are unfamiliar to me. A difficult thing for me is explaining scope of