similar to: proto and baseenv()

eapply() works on most environments, but not on baseenv(). For example, > x <- 1 > eapply(globalenv(), function(x) x) $x [1] 1 > eapply(baseenv(), function(x) x) list() I'm probably not going to have time to work on this before 2.3.0, but I don't think it's really urgent; if no one else fixes it first I'll do it after the release. Duncan Murdoch

I've just committed some changes to R-devel which affect environments. Specifically: - using NULL as an environment is now deprecated: use baseenv() instead. (baseenv() is already available in R 2.2.0, where it returns NULL. For most purposes it retains the same meaning in R-devel.) If you do use NULL, it will be converted to baseenv(), and a warning printed. For example: > f

Thank you for your suggestion. I do know how to work around the issue. I usually build a fresh environment as a child of base-environment and then insurt the weights there. I was just trying to provide an example of the issue. emptyenv() can not be used, as it is needed for the eval (errors out even if weights are not used with "could not find function list"). For some applications

Hi, this relates to the question "How to set a former environment?" asked yesterday. What is the best way to to return a function with a minimal environment from a function? Here is a dummy example: foo <- function(huge) { scale <- mean(huge) function(x) { scale * x } } fcn <- foo(1:10e5) The problem with this approach is that the environment of 'fcn' does not

I wish I had started with "I am disappointed that lm() doesn't continue its search for weights into the calling environment" or "the fact that lm() looks only in the formula environment and data frame for weights doesn't seem consistent with how other values are treated." But I did not. So I do apologize for both that and for negative tone on my part. Simplified

Hi R-devel, The following code: all.equal(baseenv(), baseenv()) gives the error when run in a clean R session with latest R-devel (r66650): kevin:~$ R --vanilla --slave -e "all.equal(baseenv(), baseenv())" Error in all.equal.envRefClass(target[[i]], current[[i]], check.attributes = check.attributes, : attempt to apply non-function Calls: all.equal ...

Dear R-Devel subscriber, first, let me express my thank to the R-Core team for the new release! I appreciate their efforts and time spent to enhance R. In accordance with the 'NEWS' file (see excerpt of it below), [... o Changed the environment tree to be rooted in an empty environment, available as emptyenv(). baseenv() has been modified to return an environment with emptyenv() as

Dear R-Devel subscriber, first, let me express my thank to the R-Core team for the new release! I appreciate their efforts and time spent to enhance R. In accordance with the 'NEWS' file (see excerpt of it below), [... o Changed the environment tree to be rooted in an empty environment, available as emptyenv(). baseenv() has been modified to return an environment with emptyenv() as

https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16660 Here is the bug, which R.home may generate a path contains a whitespace. this will cause Rcpp failed executing sourceCpp > sourceCpp("b:/2018-12-14/src/18020/MCMC.cpp") Error in system(cmd, intern = !showOutput) : 'D:/Program' not found Error in system(cmd, ignore.stderr = TRUE, intern = TRUE) :

I?m wondering which is the most efficient (time, than memory usage) way to obtain a multivariate time series object from a data frame (the easiest data structure to get data from a database trough RODBC). I have a starting point using timeSeries or xts library (these libraries can handle time zones), below you can find code to test. Merging parallelization (cbind) is something I?m thinking at

On 10/08/2020 1:42 p.m., John Mount wrote: > I wish I had started with "I am disappointed that lm() doesn't continue its search for weights into the calling environment" or "the fact that lm() looks only in the formula environment and data frame for weights doesn't seem consistent with how other values are treated." Normally searching is done automatically by

Buffer overflow detect in FC6-x86_64, see down. Juan. R version 2.4.0 (2006-10-03) Copyright (C) 2006 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R ? um software livre e vem sem GARANTIA ALGUMA. Voc? pode redistribu?-lo sob certas circunst?ncias. Digite 'license()' ou 'licence()' para detalhes de distribui??o. R ? um projeto colaborativo com muitos

Hi, I am trying to automate the creation of tables for some simply analyses. There are lots and lots of tables, thus the creation of a user-defined function to make and output them to excel. My problem is that some of the analyses have convergence issues, which I want captured and included in the output so the folks looking at them know how to view those estimates. I am successfully able to do

Hi! >getNamespaceExports("base") Error in ls(NULL, all = TRUE) : using 'as.environment(NULL)' is defunct getNamespaceExports function (ns) { ns <- asNamespace(ns) if (isBaseNamespace(ns)) ls(NULL, all = TRUE) else ls(getNamespaceInfo(ns, "exports"), all = TRUE) } <environment: namespace:base> One possible way to fix this could be

Hi R users! I was looking at some of the example code for the "environment" function. Here it is: e1 <- new.env(parent = baseenv()) # this one has enclosure package:base. e2 <- new.env(parent = e1) assign("a", 3, envir=e1) ls(e1) ls(e2) exists("a", envir=e2) # this succeeds by inheritance exists("a", envir=e2, inherits = FALSE)

Hello,I'm still working with this data set, and trying to fit it with a nonlinear model. Here is my data > small <- c(507680,507670,508832,510184,511272,513380,515828,519160,525046,534046,547982,567124,590208,614506,637876,656846,669054,672976,668800,656070,637136,614342,590970,570752,554480,542882,535630,531276,528682,527682,527020,526834,526802,526860) test <- glm(dnorm(x),

1. I did not attempt to sort through your voluminous code. But I suspect you are trying to reinvent wheels. 2. I don't understand this: "I've failed to find a solution after much searching of various R related forums." A web search on "error handling in R" **immediately** brought up ?tryCatch, which I think is what you want. If not, you should probably explain why it

>>>>> Kurt Hornik >>>>> on Tue, 30 Jun 2020 06:20:57 +0200 writes: >>>>> Jan Gorecki writes: >> Thank you both, You are absolutely correct that example >> should be minimal, so here it is. >> l = list(a=new.env(), b=new.env()) unique(l) >> Just for completeness, env_list during check that raises

You can capture warnings by using withCallingHandlers. Here is an example, its help file has more information. dataList <- list( A = data.frame(y=c(TRUE,TRUE,TRUE,FALSE,FALSE), x=1:5), B = data.frame(y=c(TRUE,TRUE,FALSE,TRUE,FALSE), x=1:5), C = data.frame(y=c(FALSE,FALSE,TRUE,TRUE,TRUE), x=1:5)) withWarnings <- function(expr) { .warnings <- NULL # warning handler will

tryCatch() is good for catching errors but not so good for warnings, as it does not let you resume evaluating the expression that emitted the warning. withCallingHandlers(), with its companion invokeRestart(), lets you collect the warnings while letting the evaluation run to completion. Bill Dunlap TIBCO Software wdunlap tibco.com On Tue, Mar 6, 2018 at 2:45 PM, Bert Gunter <bgunter.4567 at