This is documentation for an old release of NumPy (version 1.12.0). Read this page in the documentation of the latest stable release (version > 1.17).
numpy.fft.fftfreq¶
- numpy.fft.fftfreq(n, d=1.0)[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 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
Parameters: n : int
Window length.
d : scalar, optional
Sample spacing (inverse of the sampling rate). Defaults to 1.
Returns: f : ndarray
Array of length n containing the sample frequencies.
Examples
>>> 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, -5. , -3.75, -2.5 , -1.25])