In this article the real valued time domain signal is transformed to the frequency domain to extract some features like mean or variance.
But after transform to the frequency domain I calculate average hourly values (original measurements are 1/hour), so I need the signal in the frequency domain with the same length as the signal in the time domain.
Later I need features as real numbers (e.g. mean, variance), so I also need real numbers in the frequency domain. To this end, I think they use PSD. But after using Scipy's PSD (Welch estimation) I get much shorter array.
How can I get real valued array in the frequency domain from the signal with the same length as the original signal?
How should I use FFT / real FFT / PSD to get this (what arguments' values should I use)?
Would taking absolute values of the FFT output make sense?