[R-pkg-devel] How to get arbitrary precise inputs from R for an Rcpp package?

[Khue Tran]

Thank you Simon! This is very helpful! Regarding eigen, I found in the
Boost library the following example for arbitrary precision matrix solver:
https://github.com/boostorg/multiprecision/blob/develop/example/eigen_example.cpp.
I am not sure if the precision is fully preserved throughout the process,
but this example motivated me to try coding with the Boost library.

Best,
Khue Tran

On Fri, Jul 19, 2024 at 9:50 AM Simon Urbanek <simon.urbanek using r-project.org>
wrote:

> Khue,
>
>
> > On 19/07/2024, at 11:32 AM, Khue Tran <tran3 using kenyon.edu> wrote:
> >
> > Thank you for the suggestion, Denes, Vladimir, and Dirk. I have indeed
> > looked into Rmpfr and while the package can interface GNU MPFR with R
> > smoothly, as of right now, it doesn't have all the functions I need (ie.
> > eigen for mpfr class) and when one input decimals, say 0.1 to mpfr(), the
> > precision is still limited by R's default double precision.
> >
>
>
> Don't use doubles, use decimal fractions:
>
> > Rmpfr::mpfr(gmp::as.bigq(1,10), 512)
> 1 'mpfr' number of precision  512   bits
> [1]
> 0.100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000002
>
> As for eigen() - I'm not aware of an arbitrary precision solver, so I
> think the inputs are your least problem - most tools out there use LAPACK
> which doesn't support arbitrary precision so your input precision is likely
> irrelevant in this case.
>
> Cheers,
> Simon
>
>
>
> > Thank you for the note, Dirk. I will keep in mind to send any future
> > questions regarding Rcpp to the Rcpp-devel mailing list. I understand
> that
> > the type used in the Boost library for precision is not one of the types
> > supported by SEXP, so it will be more complicated to map between the cpp
> > codes and R. Given Rmpfr doesn't provide all necessary mpfr calculations
> > (and embarking on interfacing Eigen with Rmpfr is not a small task), does
> > taking input as strings seem like the best option for me to get precise
> > inputs?
> >
> > Sincerely,
> > Khue
> >
> > On Fri, Jul 19, 2024 at 8:29 AM Dirk Eddelbuettel <edd using debian.org>
> wrote:
> >
> >>
> >> Hi Khue,
> >>
> >> On 19 July 2024 at 06:29, Khue Tran wrote:
> >> | I am currently trying to get precise inputs by taking strings instead
> of
> >> | numbers then writing a function to decompose the string into a
> rational
> >> | with the denominator in the form of 10^(-n) where n is the number of
> >> | decimal places. I am not sure if this is the only way or if there is a
> >> | better method out there that I do not know of, so if you can think of
> a
> >> | general way to get precise inputs from users, it will be greatly
> >> | appreciated!
> >>
> >> That is one possible way. The constraint really is that the .Call()
> >> interface
> >> we use for all [1] extensions to R only knowns SEXP types which map to a
> >> small set of known types: double, int, string, bool, ...  The type used
> by
> >> the Boost library you are using is not among them, so you have to add
> code
> >> to
> >> map back and forth. Rcpp makes that easier; it is still far from
> automatic.
> >>
> >> R has packages such as Rmpfr interfacing GNU MPFR based on GMP. Maybe
> that
> >> is
> >> good enough?  Also note that Rcpp has a dedicated (low volume and
> friendly)
> >> mailing list where questions such as this one may be better suited.
> >>
> >> Cheers, Dirk
> >>
> >> [1] A slight generalisation. There are others but they are less common /
> >> not
> >> recommended.
> >>
> >> --
> >> dirk.eddelbuettel.com | @eddelbuettel | edd using debian.org
> >>
> >
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> >
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> > https://stat.ethz.ch/mailman/listinfo/r-package-devel
> >
>
>

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