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, 16, 'Sigma'), (16, 30, 'Beta'), (30, 40, 'Gamma')], relative=True)#
Compute the average power of the EEG in specified frequency band(s) given a pre-computed PSD.
Added 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.welchfor more details.- freqsarray_like
Array of frequencies.
- ch_nameslist
List of channel names, e.g. [‘Cz’, ‘F3’, ‘F4’, …]. If None, channels will be labelled [‘CHAN000’, ‘CHAN001’, …].
- 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