Do you know how this (forward automatic differentiation implementation)
will compare to autograd [1] or ForwardDiff.jl [2]? Can for example
autograd be used as some sort of a backend?
There is also the "tutorial implementation" autodidact [3] which seems
relevant.
Regards,
TB
[1] https://github.com/HIPS/autograd/
[2] https://github.com/JuliaDiff/ForwardDiff.jl
[3] https://github.com/mattjj/autodidact
On 24/04/2019 2:33, Nisoli Isaia wrote:
Thank you!
I think I could start by exposing these ARB functions to SAGE,
so that the interface is more complete, and then try to do the same
for Real Interval.
Best wishes
Isaia
On Monday, April 22, 2019 at 4:59:36 AM UTC-3, Marc Mezzarobba wrote:
Nisoli Isaia wrote:
> P.<x>=CBF[]
> x._sin_series(4)
Indeed, I remembered wrong. Only a few of these arb functions are
accessible from sage at this point. It is trivial to add more, though.
The relevant files are
src/sage/libs/arb/acb_poly.pxd
src/sage/rings/polynomial/polynomial_complex_arb.pyx
Also, contrary to what I said, we only have an implementation based on
arb for the case of complex coefficients. Again, it wouldn't be hard
(but maybe a bit tedious) to implement real polynomials on the same
model.
Sorry for the incorrect information!
--
Marc
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