numpy.fft.fftfreq#

fft.fftfreq(nd=1.0device=None)[source]#

Return the Discrete Fourier Transform sample frequencies.

The returned float array f contains the frequency bin centers in cycles per unit of the sample spacing (with zero at the start). For instanceif the sample spacing is in secondsthen 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

Parameters:

nint: Window length.
dscalaroptional: Sample spacing (inverse of the sampling rate). Defaults to 1.
devicestroptional: The device on which to place the created array. Default: None. For Array-API interoperability onlyso must be "cpu" if passed.

New in version 2.0.0.

Returns:

fndarray: Array of length n containing the sample frequencies.

Examples

>>> import numpy as np
>>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5], dtype=float)
>>> fourier = np.fft.fft(signal)
>>> n = signal.size
>>> timestep = 0.1
>>> freq = np.fft.fftfreq(n, d=timestep)
>>> freq
array([ 0.   1.25 2.5 ...-3.75-2.5 -1.25])