similar to: Qs: The list of arguments, wrapping functions...

Hi Frederick, I described what I meant in the post I sent to R-help (https://stat.ethz.ch/pipermail/r-help/2016-September/442174.html), but in brief, by "zero overhead" I mean that the only thing needed for library code to be accessible to client code is for it to be located in designed directory. No additional meta-files, packaging/compiling, etc. are required. Best, G. On Sun, Oct

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

I'm an experienced programmer, but learning R is making me lose the little hair I have left... > list(NULL) [[1]] NULL > length(list(NULL)) [1] 1 > x <- list() > x[[1]] <- NULL > x list() > length(x) [1] 0 >From the above experiment, it is clear that, although one can create a one-element list consisting of a NULL element, one can't get the same result by

On Mon, Oct 3, 2016 at 10:18 AM, <frederik at ofb.net> wrote: > Hi Kynn, > > Thanks for expanding. > > I wrote a function like yours when I first started using R. It's > basically the same up to your "new.env()" line, I don't do anything > with environmentns. I just called my function "mysource" and it's > essentially a "source

Hi! I'm new to R programming, though I've been programming in other languages for years. One thing I find most frustrating about R is how difficult it is to use Google (or any other search tool) to look for answers to my R-related questions. With languages with even slightly more distinctive names like Perl, Java, Python, Matlab, OCaml, etc., usually including the name of the language

Consider the following simple C program: /*** hello_r.c ***/ #include <Rinternals.h> SEXP hello() { return mkString("Hello, world!\n"); } int main(void) { SEXP x = hello(); return x == NULL; /* i.e. 0 on success */ } This program segfaults: % myR/bin/R CMD LINK gcc -I./R-2.9.0/src/include -L./myR/lib64/R/lib -lR hello_r.c -o hello_r > /dev/null % hello_r zsh:

Here's a simple example of the type of function I'm trying to write, where the first argument is a list of functions: myfun <- function(funlist, vec){ tmp <- lapply(funlist, function(x)do.call(x, args = list(vec))) names(tmp) <- names(funlist) tmp } > myfun(list("Summation" = sum, prod, "Absolute value" = abs), c(1, 4, 6, 7)) $Summation [1]

Suppose I have f1 <- function(x) x f2 <- function(x) x^2 funlist <- list(f1,f2) Then I would like to evaluate funlist such that when x is 10 I should get a list with 10 and 100. A naive way of doint this is myf <- funlist[[1]] do.call(paste(quote(myf)), list(x=10)) myf <- funlist[[2]] do.call(paste(quote(myf)), list(x=10)) - but there has to be much

Hi, everyone. I'm trying to debug an R-module, written in C, and I'm using gdb for this. How can I print "standard" R objects from within C code? BTW, I'm familiar with the advice to use R_PV given in Writing R Extensions, but it's not working for me. E.g., I get (gdb) p R_PV(x) $1 = void and yet (gdb) p *x $2 = {sxpinfo = {type = 16, obj = 0, named = 0, gp = 0,

On 10/03/2016 01:51 PM, Kynn Jones wrote: > Thank you all for your comments and suggestions. > > @Frederik, my reason for mucking with environments is that I want to > minimize the number of names that import adds to my current > environment. For instance, if module foo defines a function bar, I > want my client code to look like this: > > import("foo") >

Hi interested readers, I have a function that creates several functions within a loop and I would like them to be returned for further use as follows: Main.Function(df,...){ # df is a multivariate data funcList<-list(NULL) for (i in 1:ncol(df)){ temp<-logspline(df[,i],...) # logspline density estimate funcList[[i]]<-function(x){expression(temp,x)} } return(funcList) } I have tried

Let me preface my question by stressing that I am much less interested in the answer than in learning a way I could have *found the answer myself*. (As helpful as the participants in this list are, I have far too many R-related questions to resolve by posting here, and as I've written before, in my experience the R documentation has not been very helpful, but I remain hopeful that I may have

As &qs->qs_lock is also acquired by the timer o2net_idle_timer() which executes under softirq context, code executing under process context should disable irq before acquiring the lock, otherwise deadlock could happen if the process context hold the lock then preempt by the timer. Possible deadlock scenario: o2quo_make_decision (workqueue) -> spin_lock(&qs->qs_lock);

As &qs->qs_lock is also acquired by the timer o2net_idle_timer() which executes under softirq context, code executing under process context should disable irq before acquiring the lock, otherwise deadlock could happen if the process context hold the lock then preempt by the timer. Possible deadlock scenario: o2quo_make_decision (workqueue) -> spin_lock(&qs->qs_lock);

I'm confused by this: > identical(function() {}, function() {}) [1] FALSE Yet, after loading the Matrix package (which redefines det), the following is checked (in library.checkConflicts): > identical(get("det", baseenv()), get("det", asNamespace("Matrix")), ignore.environment=T) [1] TRUE I've looked at the code in identical.c and for closures it

Hi! I'm working on a package that must convert data to and from JSON. For this, it can use either the rjson package, or preferably, the faster RJSONIO package. I have two related questions about this. First, how can I specify that the package depends on *either* RJSONIO *or* rjson? (I.e. both are not required.) Second, what's the best-practice R idiom for such conditional loading?

Is there a *fast* converter between JSON and R? I'm aware of the rjson package, but it is implemented in R, and it is too slow for my purposes. TIA! kynn [[alternative HTML version deleted]]

I'm in the process of coding a parser (in C) to generate R entities (vectors, lists, etc.) from a text description (different from R). The basic parser works, and now I need to tell it how to create R entities. I need to be able to create character vectors (for unicode strings), integers, floats, unnamed lists, named lists, boolean values, and NA. With the exception of the two types of lists

When converting from JSON to R it seems logical that a JSON array would correspond to an "unnamed" R list, while a JSON object would correspond to a "named" R list. E.g. JSON: [1, 3.1415927, "foo", false, null] => R: list(1, 3.1415927, "foo", FALSE, NA); and JSON { "int": 1, "float": 3.1415927, "string": "foo",

On Apr 4, 2015, at 7:19 PM, Richard Flint <richard.flint at gmail.com> wrote: > More extensive debugging by running the driver sudo ./nutdrv_qx -u root -a MY_UPS -DDDDDD indicates the driver works normally then will randomly stop working at stop "send: QS". The debug logs show values successfully retrieved repeatedly until something like: > .... > Quick update... >