Do you need to run eigen() on an arbitrary matrix or symmetric one ?
best
Vladimir Dergachev
On Fri, 19 Jul 2024, Khue Tran wrote:
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.urba...@r-project.org>
wrote:
Khue,
On 19/07/2024, at 11:32 AM, Khue Tran <tr...@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 <e...@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 | e...@debian.org
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