The people who work on this will go straight to heaven, no questions asked.
Generates numpy/fft_plot.svg, the plot of with 25 points and its DFT.
Figure 1.
DFT of with 25 points
. Source code at: numpy/fft_plot.py.
Output:
sin(t)
fft
real 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
imag 0 -10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10
rfft
real 0 0 0 0 0 0 0 0 0 0 0
imag 0 -10 0 0 0 0 0 0 0 0 0

sin(t) + sin(4t)
fft
real 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
imag 0 -10 0 0 -10 0 0 0 0 0 0 0 0 0 0 0 10 0 0 10
rfft
real 0 0 0 0 0 0 0 0 0 0 0
imag 0 -10 0 0 -10 0 0 0 0 0 0
With our understanding of the discrete Fourier transform we see clearly that:
  • the signal is being decomposed into sinusoidal components
  • because we are doing the Discrete Fourier transform of a real signal, for the fft, so there is redundancy in the. We also understand that rfft simply cuts off and only keeps half of the coefficients

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