rfftfreq(n, d=1.0, chunks='auto')
This docstring was copied from numpy.fft.rfftfreq.
Some inconsistencies with the Dask version may exist.
The returned float array f contains the frequency bin centers in cycles per unit of the sample spacing (with zero at the start). For instance, if the sample spacing is in seconds, then the frequency unit is cycles/second.
Given a window length n and a sample spacing d:
f = [0, 1, ..., n/2-1, n/2] / (d*n) if n is even f = [0, 1, ..., (n-1)/2-1, (n-1)/2] / (d*n) if n is odd
Unlike fftfreq
(but like scipy.fftpack.rfftfreq
) the Nyquist frequency component is considered to be positive.
Window length.
Sample spacing (inverse of the sampling rate). Defaults to 1.
Array of length n//2 + 1
containing the sample frequencies.
Return the Discrete Fourier Transform sample frequencies (for usage with rfft, irfft).
>>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5, -3, 4], dtype=float) # doctest: +SKIPThis example is valid syntax, but we were not able to check execution
... fourier = np.fft.rfft(signal) # doctest: +SKIP
... n = signal.size # doctest: +SKIP
... sample_rate = 100 # doctest: +SKIP
... freq = np.fft.fftfreq(n, d=1./sample_rate) # doctest: +SKIP
... freq # doctest: +SKIP array([ 0., 10., 20., ..., -30., -20., -10.])
>>> freq = np.fft.rfftfreq(n, d=1./sample_rate) # doctest: +SKIPSee :
... freq # doctest: +SKIP array([ 0., 10., 20., 30., 40., 50.])
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