[SciPy-user] test_fft, test_ifft results
Darren Dale
dd55 at cornell.edu
Sat Dec 10 17:57:16 EST 2005
I have been wondering about the results of fftpack.basic.test_basic.test_fft,
fftpack.basic.test_basic.test_fftn and fftpack.basic.test_basic.test_ifft. On
my system, with scipy built against fftw2 or 3, ffts of complex input takes
over 8 times as long as real input. I dont see the same behavior with fftn.
Does anyone else see this?
Thanks,
Darren
bench_random (scipy.fftpack.basic.test_basic.test_fft)
Fast Fourier Transform
=================================================
| real input | complex input
-------------------------------------------------
size | scipy | Numeric | scipy | Numeric
-------------------------------------------------
100 | 0.18 | 0.16 | 1.51 | 0.17 (secs for 7000 calls)
1000 | 0.18 | 0.21 | 1.52 | 0.22 (secs for 2000 calls)
256 | 0.35 | 0.34 | 2.90 | 0.33 (secs for 10000 calls)
512 | 0.52 | 0.54 | 4.40 | 0.57 (secs for 10000 calls)
1024 | 0.09 | 0.10 | 0.70 | 0.10 (secs for 1000 calls)
2048 | 0.16 | 0.19 | 1.37 | 0.21 (secs for 1000 calls)
4096 | 0.16 | 0.22 | 1.24 | 0.22 (secs for 500 calls)
8192 | 0.35 | 0.63 | 2.56 | 0.71 (secs for 500 calls)
... ok
check_definition (scipy.fftpack.basic.test_basic.test_fft) ... ok
check_djbfft (scipy.fftpack.basic.test_basic.test_fft) ... ok
check_n_argument_real (scipy.fftpack.basic.test_basic.test_fft) ... ok
bench_random (scipy.fftpack.basic.test_basic.test_fftn)
Multi-dimensional Fast Fourier Transform
===================================================
| real input | complex input
---------------------------------------------------
size | scipy | Numeric | scipy | Numeric
---------------------------------------------------
100x100 | 0.15 | 0.20 | 0.14 | 0.21 (secs for 100 calls)
1000x100 | 0.11 | 0.19 | 0.10 | 0.17 (secs for 7 calls)
256x256 | 0.22 | 0.26 | 0.21 | 0.27 (secs for 10 calls)
512x512 | 0.26 | 0.32 | 0.26 | 0.33 (secs for 3 calls)
... ok
check_axes_argument (scipy.fftpack.basic.test_basic.test_fftn) ... ok
check_definition (scipy.fftpack.basic.test_basic.test_fftn) ... ok
check_shape_argument (scipy.fftpack.basic.test_basic.test_fftn) ... ok
check_shape_axes_argument (scipy.fftpack.basic.test_basic.test_fftn) ... ok
bench_random (scipy.fftpack.basic.test_basic.test_ifft)
Inverse Fast Fourier Transform
===============================================
| real input | complex input
-----------------------------------------------
size | scipy | Numeric | scipy | Numeric
-----------------------------------------------
100 | 0.18 | 0.50 | 1.88 | 0.51 (secs for 7000 calls)
1000 | 0.19 | 0.63 | 1.65 | 0.62 (secs for 2000 calls)
256 | 0.36 | 1.10 | 3.36 | 1.10 (secs for 10000 calls)
512 | 0.57 | 1.85 | 4.81 | 1.77 (secs for 10000 calls)
1024 | 0.10 | 0.32 | 0.86 | 0.32 (secs for 1000 calls)
2048 | 0.17 | 0.61 | 1.40 | 0.61 (secs for 1000 calls)
4096 | 0.18 | 0.64 | 1.44 | 0.67 (secs for 500 calls)
8192 | 0.39 | 1.58 | 2.75 | 1.58 (secs for 500 calls)
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