Re: [Numpy-discussion] Numpy Documentation: How-to content

[Ralf Gommers]

On Mon, Jun 1, 2020 at 8:18 PM Ryan C. Cooper 
wrote:

> > This sounds fantastic.
>
> Great!
>
> > In what context would the students be creating the notebooks -- as
> > part of one of your existing ME courses, as a for-credit project, as a
> > supervised but non-credit project?
>
> These would be supervised projects either for work-study or credit.
>
> > What were your thoughts on submission workflow? You review initially,
> > then the student directly submits a PR?
>
> My plan was to mentor the initial idea and creation and help the students
> submit
> PRs. For most, this will be their first interaction with Github.
>
> > Suppose several students want to create a notebook on the same topic.
> > Would you steer them to another topic, allow them to work
> > independently and both submit (and we merge best of both), urge them
> > to collaborate?
>
> My hope would be students that are passionate about the same topic could
> collaborate. I've had students collaborate on topic ideas for small
> projects
> that worked very well.
>
> > Were you planning to keep the mechanical engineering context for these
> > problems, or present abstractly?
>
> I would plan to keep the How-to as an engineering application. It shouldn't
> detract from the underlying numerical work.
>

This is something we've discussed before. It would be very useful to have
such engineering applications. +1 for your proposal.

Cheers,
Ralf
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Re: [Numpy-discussion] Numpy FFT normalization options issue (addition of new option)

[Chris Vavaliaris]

Hello,

- my first reaction would be that the less argument names we change at a
time the better, so that we don't confuse people or cause codes written with
previous NumPy versions to break. Personally I always think of "ortho" as
"orthonormal", which immediately brings "unit norm" to mind, but I have no
problem whatsoever with changing its name to "unitary" or maybe "unit",
which I'd probably choose if we were writing the routines from scratch. 

- In terms of the "inverse" name option, I do believe that it'd be a
confusing choice since "inverse" is used to describe the inverse FFT; if we
choose to stick with a name that's based on the fact that this scaling is
opposite to the "norm=None" option, then I'd suggest "norm=opposite" as a
better choice. However, following Ross' comment, I think we could choose a
name based on the fact that the forward transform is now scaled by `n`,
instead of the backward one as in the default "norm=None". In this case, I'd
suggest "norm=forward", which we can also nicely abbreviate to the
4-character form "norm=forw" if desirable.

Chris


Feng Yu wrote
> Hi,
> 
> 1. The wikipedia pages of CFT and DFT refer to norm='ortho' as 'unitary'.
> Since we are in general working with complex numbers, I do suggest unitary
> over ortho.
> (https://en.wikipedia.org/wiki/Fourier_transform#Other_conventions) and (
> https://en.wikipedia.org/wiki/Discrete_Fourier_transform#The_unitary_DFT)
> 
> 2. I share Chris's concern about 'inverse', but I could not come up with a
> nice name.
> 
> 3. Now that we are at this, should we also describe the corresponding
> continuum limit of FFT and iFFT in the documentation?
> 
> A paragraph doing so could potentially also help people diagnose some of
> the normalization factor errors. I assumed it is common that one needs to
> translate a CFT into DFT when coding a paper up, and the correct
> compensation to the normalization factors will surface if one does the
> math. -- I had the impression 1 / N corresponds to 1 / 2pi if the variable
> is angular frequency, but it's been a while since I did that last time.
> 
> - Yu
> 
> NumPy-Discussion mailing list

> NumPy-Discussion@

> https://mail.python.org/mailman/listinfo/numpy-discussion





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