Plot Spectrum uses a mathematical algorithm called “Fast Fourier Transformation” (“FFT”).
In simple terms, FFT splits the signal into multiple frequency bins. It then measures the amount of sound that lands in each bin.
The “Size” parameter determines the length of audio that is analyzed at a time, and the number of “bins”. For example, for a size of 512, FFT analyzes the sound in chunks of 512 samples (this is also called the “window size”), and splits the sound into “size / 2” = 256 frequency bins.
For a sample rate of 44100 Hz, the total frequency bandwidth is 22050 Hz. That is, the range of possible frequencies that can be represented by a sample rate of 44100 Hz is from 0 Hz (DC) to 22050 Hz (the Nyquist frequency).
So for a window size of 512, and a sample rate of 44100, the available frequency range (22050 Hz) is divided into 256 bins, each with a width of
22050 / 256 = 86.1328125 Hz.
Here is an example of the first part of an exported file where the window size was set to 512. Observe that the frequencies are multiples of 86.1328125
Frequency (Hz) Level (dB)
86.132812 -68.890556
172.265625 -61.266174
258.398438 -49.719128
344.531250 -20.277422
430.664062 -12.834599
516.796875 -17.457932
602.929688 -45.636292
689.062500 -58.301544
775.195312 -66.412956
861.328125 -72.453300