yasa.bandpower_from_psd

yasa.
bandpower_from_psd
(psd, freqs, ch_names=None, bands=[(0.5, 4, 'Delta'), (4, 8, 'Theta'), (8, 12, 'Alpha'), (12, 30, 'Beta'), (30, 40, 'Gamma')], relative=True)[source] Compute the average power of the EEG in specified frequency band(s) given a precomputed PSD.
New in version 0.1.5.
 Parameters
 psdarray_like
Power spectral density of data, in uV^2/Hz. Must be of shape (n_channels, n_freqs). See
scipy.signal.welch()
for more details. freqsarray_like
Array of frequencies.
 ch_nameslist
List of channel names, e.g. [‘Cz’, ‘F3’, ‘F4’, …]. If None, channels will be labelled [‘CHAN001’, ‘CHAN002’, …].
 bandslist of tuples
List of frequency bands of interests. Each tuple must contain the lower and upper frequencies, as well as the band name (e.g. (0.5, 4, ‘Delta’)).
 relativeboolean
If True, bandpower is divided by the total power between the min and max frequencies defined in
band
(default 0.5 to 40 Hz).
 Returns
 bandpowers
pandas.DataFrame
Bandpower dataframe, in which each row is a channel and each column a spectral band.
 bandpowers