fftfreq(n, d=1.0, chunks='auto')
This docstring was copied from numpy.fft.fftfreq.
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, ..., -1] / (d*n) if n is even f = [0, 1, ..., (n-1)/2, -(n-1)/2, ..., -1] / (d*n) if n is odd
Window length.
Sample spacing (inverse of the sampling rate). Defaults to 1.
Return the Discrete Fourier Transform sample frequencies.
>>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5], dtype=float) # doctest: +SKIPSee :
... fourier = np.fft.fft(signal) # doctest: +SKIP
... n = signal.size # doctest: +SKIP
... timestep = 0.1 # doctest: +SKIP
... freq = np.fft.fftfreq(n, d=timestep) # doctest: +SKIP
... freq # doctest: +SKIP array([ 0. , 1.25, 2.5 , ..., -3.75, -2.5 , -1.25])
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dask.array.fft.rfftfreq
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