Welcome to memspectrum’s documentation!
memspectrum
Package that uses maximum entropy spectral Analysis to compute the spectrum of a given time-series. The main object is MESA, that is meant to implement Burg Algorithm for the computation of the power spectral density.
For more information, take a look at:
Basic usage (to compute the spectrum of a given time series):
import memspectrum
M = memspectrum.MESA()
M.solve(time_series) #perform the analysis on the given time series (a real/complex np.array)
M.spectrum(dt,f) #evaluate the PSD on the given frequency grid
M.forecast(data, N_tstep) #forecast from the time series
With the proper input, this will produce this nice plot:
If you’re curious, this is the Power Spectral Density of the historical series of temperature measured around the city of Milan (Italy) with 1 hour rate. Data are taken from Copernicus. You can clearly see that the temperatures are very nicely correlated with themselfs on a day timescale. This amounts to a large peak at a frequency of 1 per hour and its multiples.
You can find this and many other examples around this documentation. For some example code, you can check the example folder of this repo.
Usage guide
Package reference
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