diff options
Diffstat (limited to 'numpy/fft/fftpack.py')
| -rw-r--r-- | numpy/fft/fftpack.py | 20 |
1 files changed, 12 insertions, 8 deletions
diff --git a/numpy/fft/fftpack.py b/numpy/fft/fftpack.py index 398eec45e..c3bb732b2 100644 --- a/numpy/fft/fftpack.py +++ b/numpy/fft/fftpack.py @@ -203,12 +203,16 @@ def ifft(a, n=None, axis=-1, norm=None): see `numpy.fft`. The input should be ordered in the same way as is returned by `fft`, - i.e., ``a[0]`` should contain the zero frequency term, - ``a[1:n/2]`` should contain the positive-frequency terms, and - ``a[n/2+1:]`` should contain the negative-frequency terms, in order of - decreasingly negative frequency. For an even number of input points, - ``A[n/2]`` represents both positive and negative Nyquist frequency. - See `numpy.fft` for details. + i.e., + + * ``a[0]`` should contain the zero frequency term, + * ``a[1:n//2]`` should contain the positive-frequency terms, + * ``a[n//2 + 1:]`` should contain the negative-frequency terms, in + increasing order starting from the most negative frequency. + + For an even number of input points, ``A[n//2]`` represents the sum of + the values at the positive and negative Nyquist frequencies, as the two + are aliased together. See `numpy.fft` for details. Parameters ---------- @@ -265,9 +269,9 @@ def ifft(a, n=None, axis=-1, norm=None): >>> n[40:60] = np.exp(1j*np.random.uniform(0, 2*np.pi, (20,))) >>> s = np.fft.ifft(n) >>> plt.plot(t, s.real, 'b-', t, s.imag, 'r--') - [<matplotlib.lines.Line2D object at 0x...>, <matplotlib.lines.Line2D object at 0x...>] + ... >>> plt.legend(('real', 'imaginary')) - <matplotlib.legend.Legend object at 0x...> + ... >>> plt.show() """ |