Hi Stefan, Thanks for the advice and for the redirection to scipy ! I will create an implementation of it there Swan BOSC. ‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐ On Friday, January 29th, 2021 at 07:49, Stefan van der Walt <stefanv@berkeley.edu> wrote:
Hi there,
Thanks for reaching out.
On Wed, Jan 27, 2021, at 04:24, Swan BOSC wrote:
Namely, the expfit function, as presented [here](https://octave.sourceforge.io/optim/function/expfit.html) (https://octave.sourceforge.io/optim/function/expfit.html) doesn't seem to exist. I'm currently building a replacement for it in my words (keywords I mean ;) ) but maybe a better solution would be to contribute some code into NumPy.
AFAIK, the preferred way to fit a Polynomial nowadays is to call numpy.polynomial.polynomial.Polynomial. Do you think that a class for `Exponential` based on that one would be an interesting addition to NumPy ?
I think Prony's method would probably be a better fit for `scipy.signal`. Please be mindful not to translate this from existing GPL code, but to implement it afresh.
Best regards, Stéfan