# skrf.network.Network.windowed¶

Network.windowed(window=('kaiser', 6), normalize=True, center_to_dc=None)[source]

Return a windowed version of s-matrix. Used in time-domain analysis.

When using time domain through s_time_db, or similar properies, the spectrum is usually windowed, before the IFFT is taken. This is done to compensate for the band-pass nature of a spectrum [1] .

This function calls scipy.signal.get_window() which gives more details about the windowing.

Parameters: window (string, float, or tuple) – The type of window to create. See scipy.signal.get_window() for details. normalize (bool) – Normalize the window to preserve power. ie sum(ntwk.s,axis=0) == sum(ntwk.windowed().s,axis=0) center_to_dc (bool or None) – If True only the positive half of the window is applied to the signal. This should be used if frequency vector begins from DC or from “close enough” to DC. If False full window is used which also attenuates low frequencies. If None then value is determined automatically based on if frequency vector begins from 0.

Examples

>>> ntwk = rf.Network('myfile.s2p')
>>> ntwk_w = ntwk.windowed()
>>> ntwk_w.plot_s_time_db()


References

 [1] Agilent Time Domain Analysis Using a Network Analyzer Application Note 1287-12