Difference between scipy periodogram and self implemented power spectral density

Question

I am trying to evaluate the frequency domain of several signals. For this I used the PSD implementation given in this answer . As a comparison I used the signal.periodogram function provided in scipy:

from scipy.signal import tukey
import scipy as sp
f, Pxx_den = sp.signal.periodogram(a_gtrend_orig,12,window=tukey( len(a_gtrend_orig) ))

However when I plot this next to the self-implemented PSD they look significantly different:

As the same window function is used and the periodogram function should also use an FFT where does this difference coming from?

Answer 1

The example that you are comparing this to, is graphing the amplitude at each frequency bin, ie, abs(fft())

The periodogram produces a power spectral density, that means it is the square of the amplitude at each frequency bin.

The label "windowed psd" is from an early edit, and was corrected later.