similar to: Problem using findVar( ) in combination with R's lazy evaluation

I'm running into some hard-to-understand behavior with the evaluation environment when NextMethod is used. I'm using square-bracket indexing into objects, and the evaluation environment of the expression inside the square brackets seems to change depending on what kind of comparison operators are used. This behavior happens when the following conditions are met (this is what I've

Hello. In the writing of my OCaml-R binding, I'm sort of confused when it comes to the use of the PROTECT and UNPROTECT macros. Basically, I have C stub functions that are in charge of calling R for everything. Here's a simple example: > CAMLprim value r_findvar (value symbol) { > /* The findVar function is defined in envir.c. It looks up a symbol > in an environment.

Dear list, I have been using "findVar" (defined in src/main/envir.c) happily and would like to use "findFun". However I have trouble when the name searched cannot be found: while "findVar" returns R_UnboundValue, "findFun" does not (the 4 last lines of "findFun" are copied below). error(_("could not find function

Hi, I am working with a very large dataset, and am using the 'filehash' package to manage such a large file. While I have no problem accessing objects that I load into a database, I was hoping there is a better way to append to objects already in the database. The only way I know now to append to an object, basically requires rewriting the entire object. Sample code:

Documentation and other bugs with postscript(): 1. This code crashes R (it asks for a font that isn't there): postscript() plot(0:1,0:1) text(0.5,0.5,'crash',font=6) The bug appears to be in the FixupFont routine in plot.c; on line 236, it checks that the font number is in the range 1..32. Later this crashes PostScriptStringWidth in devPS.c, because only fonts numbered 1..5

I've been inspired to look at the R source code by some strange timing results that I wrote about on my blog at radfordneal.wordpress.com (see the posts on "Speeding up parentheses..." and "Two surprising things...". I discovered that the strange speed advantage of curly brackets over parentheses is partially explained by an inefficiency in the evalList and

Dear all, when working on a project with embedded R, I found out that R-2.0.0 causes a problem where older versions worked OK. Rf_findVar(...) causes the following error when used to find a generic function (such as print): fun = Rf_findVar(...); R_tryEval(fun, ...); Error in function (object, ...) : Invalid generic function in usemethod Alternatively, using Rf_findFun(...) seems OK in this

Setting enviroment variable R_DEFAULT_DEVICE causes an error. The patch below fixes this. I guess the same goes for R_INTERACTIVE_DEVICE. --- R-2.7.0/src/library/grDevices/R/zzz.R 2008-04-27 13:49:11.000000000 +0200 +++ R-2.7.0/src/library/grDevices/R/zzz.R.new 2008-04-27 13:59:37.000000000 +0200 @@ -22,7 +22,7 @@ extras <- if(.Platform$OS.type == "windows")

Hi, I'm wondering if this code from the "Writing R Extensions" manual is really safe: SEXP mkans(double x) { SEXP ans; PROTECT(ans = allocVector(REALSXP, 1)); REAL(ans)[0] = x; UNPROTECT(1); return ans; } double feval(double x, SEXP f, SEXP rho) { defineVar(install("x"), mkans(x), rho);

'make check' fails on d-p-q-r-tests: > ##-- non central Chi^2 : > xB <- c(2000,1e6,1e50,Inf) > for(df in c(0.1, 1, 10)) + for(ncp in c(0, 1, 10, 100)) stopifnot(pchisq(xB, df=df, ncp=ncp) == 1) Error: pchisq(xB, df = df, ncp = ncp) == 1 is not all TRUE Execution halted Here is some more testing: xB <- c(2000,1e6,1e50,Inf) for(df in c(0.1, 1, 10)) for(ncp in c(0, 1,

Hi all, I am using R-3.0.1 under Linux platform to embed R into my C++ code. I am facing an error while executing more than 1 R-expressions parallelly. I am executing round(X) and abs(X) parallelly on a set of 50 input rows which resulted in segmentation fault after getting the following errors. Error: unprotect_ptr: pointer not found Error: argument to 'findVar' is not an environment

This question is more out of curiosity than a complaint or suggestion, but I'm just wondering. The behavior of R on calculations that result in NaN seems a bit inconsistent. # this is expected: > 0/0 [1] NaN # but this gives a warning > sin(Inf) [1] NaN Warning message: In sin(Inf) : NaNs produced # and this again does not > exp(NaN) [1] NaN Conceptually, I like to think that R

Dear R-developers, In the 'lm' documentation, the '-' operator is only specified to be used with -1 (to remove the intercept from the model). However, the documentation also refers to the 'formula' help file, which indicates that it is possible to subtract any term. Indeed, the following works with no problems (the period '.' stands for 'all terms except the

Hello, * I am setting up a backup on a Linux system with Windows XP workstations. The backup goes to three alternating usb drives, each of which is NTFS formatted. The disks should be virtually identical but they do not seem to be. First, my mount command is this (I edited a bit for brevity) mount -t ntfs-3g -o locale=nl_NL.iso-8859-1,silent /dev/disk/by-id/usb-DiskA \ /mnt/tmp || mount -t

Dear R developers, (Apologies about previous incomplete e-mail, I fat-fingered a keyboard shortcut)?? I recently upgraded to 3.2.3 and am getting mystifying errors with my in-development code (available at https://github.com/gertvv/gemtc/tree/feature/regression). Every few hundred LPs that I solve using the rcdd package will result in a SEGFAULT in the garbage collector (address 0x10, cause

Jeroen: Thank you for pointing me to ndjson, which I had not heard of and is exactly my case. My experience: jsonlite::stream_in - segfaults ndjson::stream_in - my fault, I am running Ubuntu 14.04 and it is too old so it won't compile the package corpus::read_ndjson - works!!! Of course it does a different simplification than jsonlite::fromJSON, so I have to change some code, but

If I do > example(lm) ... > mycoef <- function(object, ...) UseMethod("coef", object) > mycoef(lm.D9) Error in mycoef(lm.D9) : no applicable method for "coef" which is pretty surprising, as coef has a default method. After a bit of digging, this comes from do_usemethod having defenv = environment where the generic was defined */ defenv =

Hello Group, I could use an advice on how SEXP handles work. My aim is to implement a system where I initially set a few global variables that are used for communication between C and R code. Then I do some work with R code and periodically call a function of my own that will update the system state. Such a design is useful for many purposes (for GUIs to name one). I am not entirely sure that R

Joris, the point is that 'z' is NOT used as a predictor in the model. Therefore it should not affect predictions. Also, I find it suspicious that the error only occurs when the response variable conitains missings and 'z' is unique (I have tested several other cases to confirm this). -Mark Op vr 16 mrt. 2018 om 13:03 schreef Joris Meys <jorismeys at gmail.com>: >

Hi all, It seems that there is a use case for obtaining the environment for the "top" promise. By "top", I mean following the promise chain up the call stack until hitting a non-promise. S4 data containers often mimic the API of base R data structures. This means writing S4 methods for functions that quote their arguments, like with() and subset(). The methods package