For numpy's rfft function, the length of the output is about half of N, the length of the input sequence. What is the reason behind this? What are the frequency bins?
Check out the numpy docs ( https://docs.scipy.org/doc/numpy/reference/generated/numpy.fft.rfft.html )
To sum up, real DFT normally takes a
real input of
N samples and returns a
complex output of
What you end up with are the positive frequencies (up to the Nyquist frequency) and the negative frequencies, which are just complex conjugates of their positive counterparts, are discarded or are not even computed.