So it seems that the error only occurs in np.fft.rfft (not np.fft.fft). The following code:
import numpy as np r = np.random.RandomState(seed=0) z = r.randn(2**14).reshape((2, -1)) print(np.abs(np.fft.rfft(z)[0])[:5]) print(np.abs(np.fft.rfft(z[0]))[:5]) Prints out on a Windows 7 with Anaconda 64-bit: [ 94.22136166 149.3181169 145.77500588 177.39556729 172.05616019] [ 128.55889109 77.35670747 69.63121452 109.06772033 66.22919485] Prints out on a Ubuntu box: [ 128.55889109 77.35670747 69.63121452 109.06772033 66.22919485] [ 128.55889109 77.35670747 69.63121452 109.06772033 66.22919485] On a Windows 7 with Python(x,y): [ 128.55889109 77.35670747 69.63121452 109.06772033 66.22919485] [ 128.55889109 77.35670747 69.63121452 109.06772033 66.22919485] Brad On Thu, Nov 6, 2014 at 3:28 PM, Stefan van der Walt <ste...@sun.ac.za> wrote: > Hi Brad > > On 2014-11-07 00:51:02, Brad Buran <bbu...@alum.mit.edu> wrote: > > On Windows 7 using Anaconda with numpy 1.9.1 I get False (indicating that > > the FFT is not treating each row separately). When I test on a Ubuntu > box > > using numpy 1.9.1 I get True. Is this expected behavior? If I > understand > > the documentation correctly, the FFT on each row should be independent > > (i.e. the result should not be influenced by the other rows). > > The results should be the same. As an additional test, can you check: > > np.testing.assert_array_almost_equal(np.fft.fft(z, axis=-1)[0], > np.fft.fft(z[0])) > > Thanks > Stéfan > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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