On Fri, Dec 21, 2012 at 3:16 PM, Paul Anton Letnes <paul.anton.letnes@gmail.com> wrote:
Dear Scipy devs,
1) thanks for doing a great job in general! 2) Why is there a huge performance difference between scipy.fft and scipy.fftpack.fft? It apperars that scipy.fft == numpy.fft:
In [4]: import numpy as np
In [5]: from scipy import fft
In [6]: from scipy import fftpack
In [7]: d = np.linspace(0, 1e3, 1e7)
In [8]: %timeit np.fft.fft(d) 1 loops, best of 3: 1.29 s per loop
In [9]: %timeit fft(d) 1 loops, best of 3: 1.3 s per loop
In [10]: %timeit fftpack.fft(d) 1 loops, best of 3: 651 ms per loop
3) On a related note - what's the best performing python fft library/wrapper out there? I take it from some google research I did that e.g. fftw cannot be used due to the GPL licence.
But you could use e.g. pyfftw that will give you a better wrapper that scipy ever had for FFTW. The difference in speed is not unexpected: the fft in numpy is there for historical reasons and backward compatibility. Unless you have a very good reason not to use it, you should be using scipy.fftpack instead of numpy.fft when you can depend on scipy. regards, David