Hi Stéfan,
upd:
indeed, rfft2 has equal memory usage with our fft2d in terms of reals. thanks,
Stefan.
to this moment, i believe the results are following:
> scipy time outperformance on rectangular signals with sides of power-of-two.
> equal memory usage with rfft2
in my eyes, it's worth
Hi Stefan,
indeed you're right, the underlying formula initially was created by V.
Tutatchikov for power-of-two matrices. The initial butterfly approach requires
a recursive breakdown to 2x2 matrix in order to proceed with precalculations of
roots of unity (exactly what provides you the aforem
Hi Alexander,
On 2024-03-14 22:43:38, Alexander Levin via NumPy-Discussion
wrote:
Memory Usage -
https://github.com/2D-FFT-Project/2d-fft/blob/testnotebook/notebooks/memory_usage.ipynb
Timing comparisons(updated) -
https://github.com/2D-FFT-Project/2d-fft/blob/testnotebook/notebooks/comparis
Good day, Ralf.
I am sharing the results of the latest updates on our code. We have taken into
account the comments below and are testing the timing with %timeit -o inside
jupyter, having information about the best of 7 code passes and the average
deviation. Writing to summarise the intermediat
thanks for your extensive feedback. if i got you right, we can't state the
outperformance in all cases, because it is measured by an insufficiently
precise function and a relatively short period of time.
I understand your point of view and thank you for your observation. we will
start working o
On Tue, 12 Mar 2024 11:34:40 -
via NumPy-Discussion wrote:
> https://github.com/2D-FFT-Project/2d-fft/blob/main/notebooks/comparisons.ipynb
Hi,
Since you are using a notebook to perform the benchmark, I would advise you to
use:
```
timing = %timeit -o some_function(*args)
```
Because you
i appreciate your correction, indeed you are right, it was my fault.
i changed everything and i believe it is in the correct order of things right
now.
our current best result is
FFT:
-46%(no multithreading, no type conversions) from scipy and +0.37% is the worst
case (multithreaded, no type co
I think the argument nworkers = -1 to scipy.fft.fft2 and scipy.fft.ifft2 is
in the wrong places in the notebook.
Le lun. 11 mars 2024, à 21 h 25, via NumPy-Discussion <
numpy-discussion@python.org> a écrit :
> Good afternoon, Ralf.
>
> We have done some of the measurements you recommended, for yo
Good afternoon, Ralf.
We have done some of the measurements you recommended, for your convenience we
have created a separate folder with notebooks where we measured memory usage
and performance of our interpretation against Scipy. Separately you can run the
tests on your hardware and separately
Good evening, Ralf!
I beg your pardon, for some reason I didn't get the notification of your
response to this issue and couldn't answer in a more timely fashion.
We'll cover all the mentioned points in shortest time possible (also some
university and job projects) and I really appreciate such
On Wed, Feb 28, 2024 at 6:59 AM camrymanjr--- via NumPy-Discussion <
numpy-discussion@python.org> wrote:
> Good day!
>
> My name is Alexander Levin.
>
> My colleague and I did a project on optimisation of two-dimensional
> Fourier transform algorithm six months ago. We took your implementation of
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