mars.tensor.fft.fftfreq#
- mars.tensor.fft.fftfreq(n, d=1.0, gpu=None, chunk_size=None)[source]#
Return the Discrete Fourier Transform sample frequencies.
The returned float tensor 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
- Returns
f – Array of length n containing the sample frequencies.
- Return type
Tensor
Examples
>>> import mars.tensor as mt
>>> signal = mt.array([-2, 8, 6, 4, 1, 0, 3, 5], dtype=float) >>> fourier = mt.fft.fft(signal) >>> n = signal.size >>> timestep = 0.1 >>> freq = mt.fft.fftfreq(n, d=timestep) >>> freq.execute() array([ 0. , 1.25, 2.5 , 3.75, -5. , -3.75, -2.5 , -1.25])