Fourier transform has several usages in engineering programming. The easiest usage is producing a rolling average value for a dataset by applying a digital filter on the given values as being frequency-domain values.
A low-pass filter is the one that stops high frequency values from passing. In audio engineering, it is used to drive a sub-woofer or any low-frequency speaker. When dealing with any other numerical value, such filters become useful to have an averaged value or to cut away any interference or parasite signal in our values.
The application of a Fast Fourier Transform (FFT) on any numerical value will produce a rolling average result like this:
A rolling average with a FFT at 10hz (orange) and 4hz (red) cut frequency
A typical feature of a FFT filter is at the edges, where the filter follows the trend of the whole dataset instead of the local data. In the preceding picture, this error is visible on the right-hand side, where the FFT produces...