I've implemented the basic version of discrete Fourier Transform and I'm testing it using a pure sinusoid. However, small bumps show up in addition to the large peak. I tried Numpy.fft for this and I got the exact same height for the largest peak, so I'm pretty confident that my implementation is correct. However, I think I might be missing the step of squashing the small bumps. What tools can I use to squash them? I haven't seen anyone explicitly talk about this.

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    $\begingroup$ Can you post the code that you used? $\endgroup$ – Dan Boschen Jan 25 at 19:39
  • $\begingroup$ Where are these "bumps" on the picture in this post? $\endgroup$ – A_A Jan 25 at 20:20
  • $\begingroup$ Without your code, this question is pretty meaningless. Anyway, there's no "squashing" in any DFT – the DFT really is just that, a DFT, and your sinc-alike output reeks of you having an indexing bug in your code. $\endgroup$ – Marcus Müller Jan 25 at 21:51

A Sinc shape is the normal result for a longer FFT of a shorter finite length rectangular window of data.

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