If I understand what you're doing, your Fortran seed knows nothing about the R state. Is it possible to switch to using the R random number generators? Or can you at least use the probability integral transform to generate uniform [0, 1] via R and then convert those to observations in Fortran (that's what I did)?

Avi On Fri, Jan 17, 2020 at 7:10 PM وليد خلف معوض المطيرى <wkmtie...@qu.edu.sa> wrote: > > Hi all, > > > > I think what I’ve done is something different. Inside the Fortran subroutine, > I have a subroutine for setting the seed value of the RNG of GNU Fortran > which I think it is not related to the R RNG like the one below: > > > > subroutine initrandomseedsinr(temp) > > implicit none > > integer :: n > > integer, intent(in):: temp > > integer, dimension(:), allocatable :: seed > > > > call random_seed(size = n) > > allocate(seed(n)) > > seed = temp > > call random_seed(PUT = seed) > > deallocate(seed) > > > > end subroutine initrandomseedsinr > > , where temp is an argument of the Fortran subroutine as well as in the > wrapper R function. This will be related to the RNG method used in the GNU > Fortran that build on GCC not to the R. I am not sure if I am right on this, > but tried with using RNGkind(sample.kind = "Rounding") and it doesn’t help. > The difference in the results were not major. The output at the end of > running the functions kept having very similar results, but still have the > issue of reproducing exact results which I need it for relating work that is > based on the package. > > > > Many thanks, > > > > Waleed > > > > > > > > > > Sent from Mail for Windows 10 > > > > From: Avraham Adler > Sent: Friday, January 17, 2020 06:30 م > To: Ivan Krylov > Cc: وليد خلف معوض المطيرى; R Package Development > Subject: Re: [R-pkg-devel] For reproducibility issue > > > > Hi. > > If it helps, I call the R RNG from Fortran in my Delaporte package > [1], also using iso_c_bindings. Specifically, I have the following C > code [2]: > > void F77_SUB(unifrnd) (int *n, double *x){ > GetRNGstate(); > for (int i = 0; i < *n; ++i){ > *(x + i) = unif_rand(); > } > PutRNGstate(); > } > and call it in Fortran like so [3]: > > subroutine rdelap_f(n, a, na, b, nb, l, nl, vars) bind(C, name="rdelap_f_") > > external unifrnd > > integer(kind = c_int), intent(in), value :: n, na, nb, nl > real(kind = c_double), intent(out), dimension(n) :: vars > real(kind = c_double), intent(in) :: a(na), b(nb), l(nl) > real(kind = c_double), dimension(n) :: p > integer(kind = c_int) :: lg, lt > > call unifrnd(n, p) > lt = 1_c_int > lg = 0_c_int > call qdelap_f(p, n, a, na, b, nb, l, nl, lt, lg, vars) > > end subroutine rdelap_f > > The package passes CRAN tests (at least as of now) on anything between > GCC 4 and GCC9 [4]. > > Hope that helps, > > Avi > > [1] https://bitbucket.org/aadler/delaporte/src/master/ > [2] https://bitbucket.org/aadler/delaporte/src/master/src/utils_and_wrappers.c > [3] https://bitbucket.org/aadler/delaporte/src/master/src/delaporte.f95 > [4] https://cran.r-project.org/web/checks/check_results_Delaporte.html > > > On Fri, Jan 17, 2020 at 2:39 PM Ivan Krylov <krylov.r...@gmail.com> wrote: > > > > On Fri, 17 Jan 2020 13:55:39 +0000 > > وليد خلف معوض المطيرى <wkmtie...@qu.edu.sa> wrote: > > > > > So, does anyone have an idea of how to solve this issue. > > > > "Writing R Extensions", 1.6. Writing portable packages: > > > > >> Compiled code should not call the system random number generators > > >> such as rand, drand48 and random, but rather use the interfaces to > > >> R’s RNGs described in Random numbers. In particular, if more than > > >> one package initializes the system RNG (e.g. via srand), they will > > >> interfere with each other. > > > > >> Nor should the C++11 random number library be used, nor any other > > >> third-party random number generators such as those in GSL. > > > > It somewhat less convenient to call the R random number generator from > > Fortran than it would be from C or C++, but still possible. There is a > > F77-style example of such use [1], but since you are already using > > iso_c_binding, you should be able to declare the C API [2] right in the > > Fortran source: > > > > subroutine GetRNGState() bind(c) > > end subroutine > > > > subroutine PutRNGstate() bind(c) > > end subroutine > > > > As a bonus, you get to use the R distribution functions [3], without > > the need to implement them yourself from uniformly distributed samples: > > > > function rnorm(mu, sigma) bind(c) result(ret) > > use intrinsic, iso_c_binding, only: c_double > > real(c_double), value :: mu, sigma > > real(c_double) ret > > end function > > > > function rgamma(shape, scale) bind(c) result(ret) > > use intrinsic, iso_c_binding, only: c_double > > real(c_double), value :: shape, scale > > real(c_double) ret > > end function > > > > (The prototypes above are unchecked; I haven't written any Fortran 2003 > > in more than a year.) > > > > -- > > Best regards, > > Ivan > > > > [1]: > > https://cran.r-project.org/doc/manuals/R-exts.html#index-Random-numbers-in-Fortran > > > > [2]: https://cran.r-project.org/doc/manuals/R-exts.html#Random-numbers > > > > [3]: > > https://cran.r-project.org/doc/manuals/R-exts.html#Distribution-functions > > > > ______________________________________________ > > R-package-devel@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-package-devel > > ______________________________________________ R-package-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-package-devel