I am porting some matlab code to python using scipy and got stuck with the following line:
[Pxx, f] = periodogram(x, , 512, 5)
f, Pxx = signal.periodogram(x, 5, nfft=512)
After researching octave's and scipy's periodogram source code I found that they use different algorithm to calculate power spectral density estimate. Octave (and MATLAB) use FFT, whereas scipy's periodogram use the Welch method.
As @georgesl has mentioned, the output looks quite alike, but still, it differs. And for porting reason it was critical. In the end, I simply wrote a small function to calculate PSD estimate using
FFT, and now output is the same. According to
timeit testing, it works ~50% faster (1.9006s vs 2.9176s on a loop with 10.000 iterations). I think it's due to the FFT being faster than Welch in scipy's implementation, of just being faster.
Thanks to everyone who showed interest.