Re: [Rd] "if" function in pure R?
Hi Alexandre,
I'm not an R expert so this is only my personal thought:
I don't think you can achieve what you want exactly. A possible solution
would be defining a binary operator %*%, where you can replace the asterisk
with any function name you want. The function %*% is special since it has
two arguments, left operand and right operand respectively. You then
can call the `substitute` function to get its function arguments in an
expression format and proceed to do what you want. Here is an example to
show the idea.
*Code:*
`%myOperator%` <- function(x, y) {
x = substitute(x)
y = substitute(y)
return(list(x, y))
}
myIf(i == 1, arg1) %myOperator% {
doSomeThing
}
*Results:*
[[1]]
myIf(i == 1, arg1)
[[2]]
{
doSomeThing
}
I hope that helps.
Best,
Jiefei
On Sun, May 26, 2019 at 4:45 AM Alexandre Courtiol <
alexandre.court...@gmail.com> wrote:
> Hi all,
>
> Could anyone refer to me to a good source to learn how to program a simple
> control-flow construct* in R, or provide me with a simple example?
>
> Control-flow constructs are programmed as primitives, but I would like to
> be able to do that (if possible) in pure R.
>
> The general context is that those functions are a mystery to me. The
> motivating example is that I would like to create a function that behave
> similarly to base::`if` with an extra argument to the function (e.g. to
> include an error rate on the condition).
>
> Many thanks,
>
> Alex
>
> * control-flow constructs are functions such as if, for, while... that
> allow for call of the form fn(x) expr to work (see ?Control).
>
> --
> Alexandre Courtiol
>
> http://sites.google.com/site/alexandrecourtiol/home
>
> *"Science is the belief in the ignorance of experts"*, R. Feynman
>
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>
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[Rd] Fast way to call an R function from C++?
Hi,
I'm looking for a most efficient way to call an R function from C++ in a
package. I know there are two functions (`R_forceAndCall` and `Rf_eval`)
that can do the "call" part, but both are slow compared to calling the same
function in R. I also try to use Rcpp and it is the worse one. Here is my
test code:
C++ code:
```
// [[Rcpp::export]]
SEXP C_test1(SEXP f, SEXP x) {
SEXP call =PROTECT(Rf_lang2(f, x));
SEXP val = R_forceAndCall(call, 1, R_GlobalEnv);
UNPROTECT(1);
return val;
}
// [[Rcpp::export]]
SEXP C_test2(SEXP expr, SEXP env) {
SEXP val = Rf_eval(expr, env);
return val;
}
// [[Rcpp::export]]
SEXP C_test3(SEXP f,SEXP x) {
Function fun(f);
return fun(x);
}
```
R code:
```
testFunc<-function(x){
x=x^2
return(x)
}
evn=new.env()
evn$x=x
expr=quote(testFunc(evn$x))
testFunc(evn$x)
C_test1(testFunc, evn$x)
C_test2(expr,evn)
C_test3(testFunc,evn$x)
```
For the results, I run each function 1,000,000 times:
- testFunc : 0.47 sec
- C_test1 : 2.46 sec
- C_test2 : 2.74 sec
- C_test3 : 18.86 sec
It is clear to see that calling an R function in R is the fast one, it is
about 5X faster than ` R_forceAndCall ` and ` Rf_eval`. the latter two
functions have a similar performance and using Rcpp is the worst one. Is it
expected? Why is calling an R function from C++ much slower than calling
the function from R? Is there any faster way to do the function call in C++?
Best,
Jiefei
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Re: [Rd] Fast way to call an R function from C++?
Hello Kevin and Iñaki, Thanks for your quick responses. I sincerely appreciate them! I can see how complicated it is to interact with R in C. Iñaki's suggestion is very helpful, I saw there is a lot of performance gain by turning the flag on, but sadly the best performance it can offer still cannot beat R itself. It is interesting to see that C++ is worse than R in this special case despite there is a common belief that C++ code is the fast one... Anyway, thanks again for your suggestions and reference! Best, Jiefei On Tue, Jun 18, 2019 at 2:39 PM Iñaki Ucar wrote: > For reference, your benchmark using UNWIND_PROTECT: > > > system.time(test(testFunc, evn$x)) >user system elapsed > 0.331 0.000 0.331 > > system.time(test(C_test1, testFunc, evn$x)) >user system elapsed > 2.029 0.000 2.036 > > system.time(test(C_test2, expr, evn)) >user system elapsed > 2.307 0.000 2.313 > > system.time(test(C_test3, testFunc, evn$x)) >user system elapsed > 2.131 0.000 2.138 > > Iñaki > > On Tue, 18 Jun 2019 at 20:35, Iñaki Ucar wrote: > > > > On Tue, 18 Jun 2019 at 19:41, King Jiefei wrote: > > > > > > [...] > > > > > > It is clear to see that calling an R function in R is the fast one, it > is > > > about 5X faster than ` R_forceAndCall ` and ` Rf_eval`. the latter two > > > functions have a similar performance and using Rcpp is the worst one. > Is it > > > expected? Why is calling an R function from C++ much slower than > calling > > > the function from R? Is there any faster way to do the function call > in C++? > > > > Yes, there is: enable fast evaluation by setting > > -DRCPP_USE_UNWIND_PROTECT, or alternatively, use > > > > // [[Rcpp::plugins(unwindProtect)]] > > > > Iñaki > > > > -- > Iñaki Úcar > [[alternative HTML version deleted]] __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
[Rd] strange increase in the reference number
Hi, I just found a strange increase in the reference number and I'm wondering if there is any reason for it, here is the code. > a=c(1,2,3) > .Internal(inspect(a)) @0x1bf0b9b0 14 REALSXP g0c3 [NAM(1)] (len=3, tl=0) 1,2,3 > is.vector(a) [1] TRUE > .Internal(inspect(a)) @0x1bf0b9b0 14 REALSXP g0c3 [NAM(7)] (len=3, tl=0) 1,2,3 The variable *a* initially has one reference number, after calling *is.vector* function, the reference number goes to 7, which I believe is the highest number that is allowed in R. I also tried the other R functions, *is.atomic, is.integer* and *is.numeric* do not increase the reference number, but *typeof *will do. Is it intentional? Best, Jiefei [[alternative HTML version deleted]] __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] strange increase in the reference number
Hi Duncan, Gabriel, and Brodie
Thanks for the explanations and references. Brodie's blog talks about
exactly the same problem without involving too many technical details. I
would recommend to read it if anyone is interested in it. I really
appreciate all of you guys' answers.
Best,
Jiefei
On Sat, Jul 13, 2019 at 2:19 PM brodie gaslam via R-devel <
r-devel@r-project.org> wrote:
> Re ENSURE_NAMEDMAX, I am unsure but think this happens in (src/eval.c@492
> ):
> static SEXP forcePromise(SEXP e)
> {
> if (PRVALUE(e) == R_UnboundValue) {
> /* ... SNIP ...*/
> val = eval(PRCODE(e), PRENV(e));
> /* ... SNIP ...*/
> SET_PRSEEN(e, 0);
> SET_PRVALUE(e, val);
> ENSURE_NAMEDMAX(val); <<<<<<< HERE
> SET_PRENV(e, R_NilValue);
> }
> return PRVALUE(e);
> }
>
> as part of the evaluations of the closure. `forcePromise` is called
> ineval (src/eval.c@656). It's been a while since I've looked at the
> mechanicsof how the native version of `eval` works so I could be completely
> wrong.
>
> B.
>
> PS: line references are in r-devel@76287.
>
>
> On Friday, July 12, 2019, 4:38:06 PM EDT, Gabriel Becker <
> gabembec...@gmail.com> wrote:
>
>
>
>
>
> Hi Jiefei and Duncan,
>
> I suspect what is likely happening is that one of ENSURE_NAMEDMAX or
> MARK_NOT_MUTABLE are being hit for x. These used to set named to 3, but now
> set it to 7 (ie the previous and current NAMEDMAX value, respectively).
>
> Because these are macros rather than C functions, its not easy to figure
> out why one of them is being invoked from do_isvector (a cursory
> exploration didn't reveal what was going on, at least to me) and I don't
> have the time to dig super deeply into this right now, but perhaps Luke or
> Tomas know why this is happening of the top of their head.
>
> Sorry I can't be of more help.
>
> ~G
>
>
>
> On Fri, Jul 12, 2019 at 11:47 AM Duncan Murdoch
> wrote:
>
> > On 12/07/2019 1:22 p.m., King Jiefei wrote:
> > > Hi,
> > >
> > > I just found a strange increase in the reference number and I'm
> wondering
> > > if there is any reason for it, here is the code.
> > >
> > >> a=c(1,2,3)
> > >> .Internal(inspect(a))
> > > @0x1bf0b9b0 14 REALSXP g0c3 [NAM(1)] (len=3, tl=0) 1,2,3
> > >> is.vector(a)
> > > [1] TRUE
> > >> .Internal(inspect(a))
> > > @0x1bf0b9b0 14 REALSXP g0c3 [NAM(7)] (len=3, tl=0) 1,2,3
> > >
> > > The variable *a* initially has one reference number, after calling
> > > *is.vector* function, the reference number goes to 7, which I believe
> is
> > > the highest number that is allowed in R. I also tried the other R
> > > functions, *is.atomic, is.integer* and *is.numeric* do not increase the
> > > reference number, but *typeof *will do. Is it intentional?
> >
> > is.vector() is a closure that calls .Internal. is.atomic(),
> > is.integer() and is.numeric() are all primitives.
> >
> > Generally speaking closures that call .Internal are easier to implement
> > (e.g. is.vector can use the regular mechanism to set a default for its
> > second argument), but less efficient in CPU time. From it's help page,
> > it appears that the logic for is.vector() is a lot more complex than for
> > the others, so that implementation does make sense.
> >
> > So why does NAMED go to 7? Initially, the vector is bound to a. Within
> > is.vector, it is bound to the local variable x. At this point there are
> > two names bound to the same object, so it has to be considered
> > immutable. There's really no difference between any of the values of 2
> > or more in the memory manager. (But see
> > http://developer.r-project.org/Refcnt.html for some plans. That
> > document is from about 5 years ago; I don't know the current state.)
> >
> > Duncan Murdoch
> >
> > __
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> >
>
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Re: [Rd] ALTREP wrappers and factors
Hi Kylie,
For your question, I don't think a wrapper can completely solve your
problem. The duplication occurs since your variable y has more than 1
reference number( Please see highlighted), so even you have a wrapper, any
changes on the value of the wrapper still can trigger the duplication.
> .Internal(inspect(y))
> @7fb0ce78c0f0 13 INTSXP g0c0 *[NAM(7)]* matter vector (mode=3, len=3,
> mem=0)
My guess is that *matter:::as.altrep* function assigned the variable *y* to
a local variable so that it increases the reference number. For example:
*This would not cause a duplication*
> > a=c(1,2,3)
> > .Internal(inspect(a))
> @0x2384f530 14 REALSXP g0c3 [NAM(1)] (len=3, tl=0) 1,2,3
> > attr(a,"dim")=c(1,3)
> > .Internal(inspect(a))
> @0x2384f530 14 REALSXP g0c3 [NAM(1),ATT] (len=3, tl=0) 1,2,3
> ATTRIB:
> @0x23864b58 02 LISTSXP g0c0 []
> TAG: @0x044b1a90 01 SYMSXP g1c0 [MARK,LCK,gp=0x4000] "dim"
> (has value)
> @0x2384cb48 13 INTSXP g0c1 [NAM(7)] (len=2, tl=0) 1,3
>
*This would cause a duplication, even though the function test does
nothing.*
> > test<-function(x) x1=x
> > a=c(1,2,3)
> > .Internal(inspect(a))
> @0x2384f260 14 REALSXP g0c3 [NAM(1)] (len=3, tl=0) 1,2,3
> > test(a)
> > .Internal(inspect(a))
> @0x2384f260 14 REALSXP g0c3 [NAM(7)] (len=3, tl=0) 1,2,3
> > attr(a,"dim")=c(1,3)
> > .Internal(inspect(a))
> @0x2384f0d0 14 REALSXP g0c3 [NAM(1),ATT] (len=3, tl=0) 1,2,3
> ATTRIB:
> @0x238666c0 02 LISTSXP g0c0 []
> TAG: @0x044b1a90 01 SYMSXP g1c0 [MARK,LCK,gp=0x4000] "dim"
> (has value)
> @0x2384c6e8 13 INTSXP g0c1 [NAM(7)] (len=2, tl=0) 1,3
>
If that is the case and you are 100% sure the reference number should be 1
for your variable *y*, my solution is to call *SET_NAMED *in C++ to reset
the reference number. Note that you need to unbind your local variable
before you reset the number. To return an unbound SEXP, the C++ function
should be placed at the end of your *matter:::as.altrep *function. I don't
know if there is any simpler way to do that and I'll be happy to see any
opinion.
Also, I notice that you are using ALTREP to create a wrapper for your
*matter_vec *class. I'm an author of AltWrapper package and the package is
able to define an ALTREP in pure R level, it is capable to add an attribute
to ALTREP object when creating the object and has a correct reference
number. The simplest example would be
*CODE*
```
library(AltWrapper)
inspectFunc <- function(x) cat("Altrep object\n")
lengthFunc <- function(x) return(length(x))
getPtrFunc <- function(x, writeable) return(x)
setAltClass(className = "test", classType = "real")
setAltMethod(className = "test", inspect = inspectFunc)
setAltMethod(className = "test", getLength = lengthFunc)
setAltMethod(className = "test", getDataptr = getPtrFunc)
A = runif(6)
A_alt = makeAltrep(className = "test", x = A, *attributes = list(dim = c(2,
3))*)
```
*RESULT*
```
> .Internal(inspect(A_alt))
@0x2385ac00 14 REALSXP g0c0 [NAM(1),ATT] Altrep object
ATTRIB:
@0x2385a8b8 02 LISTSXP g0c0 []
TAG: @0x044b1a90 01 SYMSXP g1c0 [MARK,LCK,gp=0x4000] "dim" (has
value)
@0x2384d590 13 INTSXP g0c1 [NAM(7)] (len=2, tl=0) 2,3
> A_alt
[,1] [,2] [,3]
[1,] 0.9430458 0.548670 0.4148741
[2,] 0.9550899 0.251857 0.6077540
```
I will be happy to talk more about it if you are interested in the package,
it is available at
https://github.com/Jiefei-Wang/AltWrapper
Best,
Jiefei
On Thu, Jul 18, 2019 at 3:28 AM Bemis, Kylie
wrote:
> Hello,
>
> I’m experimenting with ALTREP and was wondering if there is a preferred
> way to create an ALTREP wrapper vector without using
> .Internal(wrap_meta(…)), which R CMD check doesn’t like since it uses an
> .Internal() function.
>
> I was trying to create a factor that used an ALTREP integer, but
> attempting to set the class and levels attributes always ended up
> duplicating and materializing the integer vector. Using the wrapper avoided
> this issue.
>
> Here is my initial ALTREP integer vector:
>
> > fc0 <- factor(c("a", "a", "b"))
> >
> > y <- matter::as.matter(as.integer(fc0))
> > y <- matter:::as.altrep(y)
> >
> > .Internal(inspect(y))
> @7fb0ce78c0f0 13 INTSXP g0c0 [NAM(7)] matter vector (mode=3, len=3, mem=0)
>
> Here is what I get without a wrapper:
>
> > fc1 <- structure(y, class="factor", levels=levels(x))
> > .Internal(inspect(fc1))
> @7fb0cae66408 13 INTSXP g0c2 [OBJ,NAM(2),ATT] (len=3, tl=0) 1,1,2
> ATTRIB:
> @7fb0ce771868 02 LISTSXP g0c0 []
> TAG: @7fb0c80043d0 01 SYMSXP g1c0 [MARK,LCK,gp=0x4000] "class" (has
> value)
> @7fb0c9fcbe90 16 STRSXP g0c1 [NAM(7)] (len=1, tl=0)
> @7fb0c80841a0 09 CHARSXP g1c1 [MARK,gp=0x61] [ASCII] [cached]
> "factor"
> TAG: @7fb0c8004050 01 SYMSXP g1c0 [MARK,NAM(7),LCK,gp=0x4000] "levels"
> (has value)
> @7fb0d1dd58c8 16 STRSXP g0c2 [MARK,NAM(7)] (len=2, tl=0)
> @7fb0c81bf4c0 09 CHARSXP g1c1 [MARK,gp=0x61]
