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
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
