rfftfreq(n, d=1.0)
The returned float array contains the frequency bins in cycles/unit (with zero at the start) given a window length n and a sample spacing d:
f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2]/(d*n) if n is even
f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2,n/2]/(d*n) if n is odd
DFT sample frequencies (for usage with rfft, irfft).
import numpy as np
from scipy import fftpack
sig = np.array([-2, 8, 6, 4, 1, 0, 3, 5], dtype=float)
sig_fft = fftpack.rfft(sig)
n = sig_fft.size
timestep = 0.1
freq = fftpack.rfftfreq(n, d=timestep)
freq
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.fft._basic:fft
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