Just a note to avoid confusion: ForwardDiff.jl doesn't use complex numbers
at all. It uses its own implementation of dual number/hyper-dual number
"ensembles" for computing multiple partial derivatives simultaneously.
There is no additional error term in ForwardDiff.jl's formulation.
--
Hi Nitin,
Thanks for the note and references. The recent upgrade of ForwardDiff.jl
certainly shows the value of these methods.
Did you (re-)implement MultiComplexNumbers from the 2nd reference, or used one
of the two (Fortran and Matlab) prototype modules? Did you use it from within
Julia? Do
There is another method to calculate any order derivatives, very similar to
this one, known as Multi-complex differentiation. This method can calculate
derivatives up-to any order.
Cool. I took a quick look over the code, and it looks pretty good to me.
You have an inline comment about wanting understand convert/promote
better--one good place to look is promotions.jl in base:
https://github.com/JuliaLang/julia/blob/master/base/promotion.jl#L158
This defines some fairly
Thank you very much Jason, great feedback.
I will work through your suggestions and make the changes.
In particular the extensibility argument/pattern is something I've been
thinking about as well.
Regards,
Rob J. Goedman
goed...@icloud.com
On Mar 30, 2014, at 10:09 AM, Jason Merrill
