Connected with this topic , I would like to have some clarifications about the Fourier Transform and the Python tools that make it.
Having my data set whose plot is showed in the above link, my array of data is stored in
rate. Then, if I check the result from the Fourier transform:
yfft = np.fft.rfft(rate) y_smooth = np.fft.irfft(yfft) print y_smooth
[ 3.20000028e+01+0.j -7.92633533e+00-7.75032655j -5.34245688e+00-3.82390808j -2.39880935e+00-0.60037314j -8.71249166e-01-0.04362804j -8.52507194e-02+1.09973189j -1.58332047e-01+1.15256295j -3.38909974e-01+0.96327143j 5.51323015e-02+0.43936749j 3.81205886e-01-0.02489853j 2.99110153e-01-0.26319101j 3.28283652e-01+0.11668814j 1.08849205e-02-0.11317937j 3.79952011e-01+0.22278952j 7.37720998e-02-0.26810083j -2.14247586e-01-0.25950865j -1.32242152e-01+0.j ]
So, I am quite confused about this result, and I would need some tips how to interpret these numbers.
1) The array contains $17$ complex number : does it mean that my signal can be approximated by a superimposition of $17$ harmonics?
2) Are these numbers the power of each harmonic, or what?
3) are they ordered by the frequency order, or by power? Let's say I want to put to zero the higher orders, which ones should I put to zero?