I am trying to utilize Numpy's
fft function, however when I give the function a simple Gaussian function the FFT of that Gaussian function is not a Gaussian, its close but its halved so that each half is at either end of the x axis.
I was told by my professor that this has something to do with how when Fourier transform from x to k space, the k space in FFT algorithms tend to start from N=0 to N=N (where N is the size of the data array) and the k in this case would go from k(0) to k(N/2) (so far k would be positive) and then beyond k(N/2) k is negative and would go to k(N) = 0. So if there was a plot of k vs N, the shape would be like a slanted N if that makes sense.
In which part of the FFT algorithm is responsible for FFT of Gaussian to not be Gaussian? How to I change to make it Gaussian? Is it the Bit reversing or Butterfly operation that is responsible?