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
Hi Brad
On 2014-11-07 00:51:02, Brad Buran 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 documentati
Given the following code:
import numpy as np
x = np.random.random(size=2**14)
y = x.copy()
z = np.concatenate([x[np.newaxis], y[np.newaxis]], axis=0)
print(np.all(np.fft.fft(z, axis=-1)[0] == np.fft.fft(z[0])))
On Windows 7 using Anaconda with numpy 1.9.1 I get False (indicating that
the FFT is n
