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On the use of adding an expfit class in or next to the polynomial module

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Swan BOSC

On the use of adding an expfit class in or next to the polynomial module

Hello people !

First-of-all, thank you for your great service to the Python community.

I'm working for a project on porting some Octave code base towards Python. As you can imagine, it is a lot of fun, but I sometimes come across functions that are not (yet ?) available in the mighty NumPy package.

Namely, the expfit function, as presented here (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 ?

Thanks in advance,

Swan BOSC.

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Stefan van der Walt

Re: On the use of adding an expfit class in or next to the polynomial module

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) 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

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Swan BOSC

Re: On the use of adding an expfit class in or next to the polynomial module

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 <[hidden email]> 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) 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

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