Dear all,
Thanks again for your answers.
For one of my project, I indeed need the special complex error
functions. This is why I used the RcppFaddeeva source files in the first
time.
This being said, it was ALSO a workaround to get access to complex
numbers operations (and so that the package compile under Windows
without errors).
I know that using .C() is now discouraged by R core group. This being
said, I am a bit reluctant, at least for some projects, to use .Call().
I like the idea to be able to use old FORTRAN77 codes and/or C codes
written by others. Usually, using these codes is quite straightforward
thanks to the .Fortran() interface. As for the C codes, it is only
necessary to modify the arguments of the C function to make them
pointers in
order to then call it through the .C() function.
My understanding, but maybe I am not good enough, is that to be able to
call a C/C++ function using .Call() and/or involving Rcpp needs
a lot more modifications to the original C source file.
I think this is bad for reproducibility. For example, if one would like
to call this same C code from Matlab and if this C code is full of Rcpp,
then
I guess there will be some trouble. Am I right?
Note that I "learned" a bit of Rcpp. I am the author and maintainer of
package PoweR:
https://cran.r-project.org/web/packages/PoweR/index.html
I wrote in this package the file calcpuissRcpp.cpp that contains some
Rcpp features (maybe you can have a quick look to see my low? level
of knowledge of Rcpp). And I agree that this is cool stuff when you want
to be able to access high level
R functions from C. But as said above, you loose some reproducibility
(in the sense explained above) and maybe also some speed (and this is why I
have two "parallel" versions in my PoweR package: calcpuiss.cpp and
calcpuissRcpp.cpp).
So, with all this in mind, my "request" is still the same. Namely being
able to manipulate (and create) complex numbers at the (pure) C level in
an R package so that it could compile properly (without errors) under
Microsoft Windows. I found this workaround by copying these RcppFaddeeva
source files
(.cpp and .h files) in the src/ directory of my package(s) but this is
not really clean. Probably I could try to remove all "unnecessary" stuff
from these source
files in order to keep only what is really needed to play with complex
numbers at the (pure) C level, but maybe there would be something more
clever to do? Like adding RcppFaddeeva to the LinkingTo/Depends/Export
fields? Or creating a very simple package (by removing all special
complex error
functions from RcppFaddeeva) and call the resulting package EnableC and
then add this to LinkingTo/Depends/Export fields?
I hope I made myself clear ...
Thank you again for your time.
Best regards,
Pierre L.
Le 03/01/2016 22:14, Dirk Eddelbuettel a écrit :
On 4 January 2016 at 09:50, Baptiste Auguie wrote:
| Hi,
|
| Just to clarify: did you include files from RcppFaddeeva because you need some
| of its functionality (special complex error functions), or was it only a
| workaround to get access to complex numbers? In the latter case, I recommend
| you try making a minimal Rcpp package to see how easy it is to interface with
| C++ functions, and that way you will only have relevant header files included.
+1
I already responded to Pierre's initial emails in November and tried then to
explain to him that that .C() is a _really bad idea at this point in time.
It is two months later and nothing has changed.
So here is a quick illustration of what Baptiste meant. All it takes is
library(Rcpp) # no other depends
and then (and I even got this right on first try):
R> cppFunction("Rcomplex addTwo(Rcomplex x, Rcomplex y) {return x + y; }")
R> addTwo(2+2i, 3+3i)
[1] 5+5i
R>
With one invocation of cppFunction() I created an ad-hoc compiled function
(technically compiled as C++ but you can call this C as well) which adds two
complex number -- one of Pierre's request as per the email below. And low
and behold is just does that.
So yes -- maybe time to learn some Rcpp, maybe forget about .C() and simply
get on with this and other other things.
Dirk
|
| Best,
|
| baptiste
|
|
|
| On 4 January 2016 at 09:36, Pierre Lafaye de Micheaux
<laf...@dms.umontreal.ca>
| wrote:
|
| Dear all,
|
| This email comes after a discussion on the R-pkg-devel mailing list:
| https://stat.ethz.ch/pipermail/r-package-devel/2016q1/000627.html
|
| My purpose was to be able, in two of my packages, to use complex numbers
| (create some, addition, multiplication, division, modulus, etc)
| directly in a C code that is called from R (using the .C interface).
| Note that these complex numbers might not come from R but could be created
| and used directly in my C code, that will then output (via pointers)
| real (I mean double) values back to R (via the .C interface). I could also
| send from R these complex numbers via the .C interface.
|
| A very simple example of such a function called from R via the .C
interface
| could be the following:
|
| #include <R.h>
| #include "Rmath.h"
| extern "C" {
| void Cfunc(complex double *var) {
| double _Complex z = 1.0 + 2.0 * _Complex_I;
| var[0] = z + exp(var[0]);
| return;
| }}
|
| I could call this function from R as follows:
| .C(1i)
|
| No problem so far when I use such a function in a package that is compiled
| under Linux. But this will not work under windows (see the discussion
| on the R-pkg-devel list). So what I did to make everything work under
| Windows also was to include in the src/ directory of my package the source
| files
| from the RcppFaddeeva package. Then I would modify the function above as
| follows:
|
| #include <R.h>
| #include "Rmath.h"
| #include "libraries/callFaddeeva.cpp"
| #include "libraries/Faddeeva.cpp"
| #include "libraries/RcppExports.cpp"
| extern "C" {
| void Cfunc(complex double *var) {
| cmplx z = C(1.0, 2.0);
| var[0] = z + cexp(var[0]);
| return;
| }}
|
| Maybe there is a way not to include all the Faddeeva source files in my
| packages? But I do not know how to do it.
|
| Best regards,
|
| Pierre L.
|
|
|
| --
| Pierre Lafaye de Micheaux
|
| Adresse courrier:
| Université de Montréal
| Pavillon André-Aisenstadt
| Département de Mathématiques et Statistique
| CP 6128 Succursale Centre-ville
| Montréal Qc H3C 3J7
| CANADA
|
| Adresse physique:
| Département de Mathématiques et Statistique
| Bureau 4249, Pavillon André-Aisenstadt
| 2920, chemin de la Tour
| Montréal, Québec H3T 1J4
| CANADA
|
| Tél.: (00-1) 514-343-6607 / Fax: (00-1) 514-343-5700
| laf...@dms.umontreal.ca
| http://www.biostatisticien.eu
|
| _______________________________________________
| Rcpp-devel mailing list
| Rcpp-devel@lists.r-forge.r-project.org
| https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
|
|
| _______________________________________________
| Rcpp-devel mailing list
| Rcpp-devel@lists.r-forge.r-project.org
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--
Pierre Lafaye de Micheaux
Adresse courrier:
Université de Montréal
Pavillon André-Aisenstadt
Département de Mathématiques et Statistique
CP 6128 Succursale Centre-ville
Montréal Qc H3C 3J7
CANADA
Adresse physique:
Département de Mathématiques et Statistique
Bureau 4249, Pavillon André-Aisenstadt
2920, chemin de la Tour
Montréal, Québec H3T 1J4
CANADA
Tél.: (00-1) 514-343-6607 / Fax: (00-1) 514-343-5700
laf...@dms.umontreal.ca
http://www.biostatisticien.eu
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