Compute power spectral density (PSD) using a multi-taper method.
array, shape=(…, n_times)The data to compute PSD from.
floatThe sampling frequency.
floatThe lower frequency of interest.
floatThe upper frequency of interest.
floatThe bandwidth of the multi taper windowing function in Hz.
Use adaptive weights to combine the tapered spectra into PSD (slow, use n_jobs >> 1 to speed up computation).
Only use tapers with more than 90% spectral concentration within bandwidth.
Normalization strategy. If “full”, the PSD will be normalized by the
sampling rate as well as the length of the signal (as in
Nitime). Default is 'length'.
strThe format of the returned psds array. Can be either 'complex'
or 'power'. If 'power', the power spectral density is returned.
If output='complex', the complex fourier coefficients are returned
per taper.
int | NoneThe number of jobs to run in parallel. If -1, it is set
to the number of CPU cores. Requires the joblib package.
None (default) is a marker for ‘unset’ that will be interpreted
as n_jobs=1 (sequential execution) unless the call is performed under
a joblib.parallel_backend() context manager that sets another
value for n_jobs.
str | int | NoneControl verbosity of the logging output. If None, use the default
verbosity level. See the logging documentation and
mne.verbose() for details. Should only be passed as a keyword
argument.
ndarray, shape (…, n_freqs) or (…, n_tapers, n_freqs)The power spectral densities. All dimensions up to the last (or the
last two if output='complex') will be the same as input.
arrayThe frequency points in Hz of the PSD.
ndarrayThe weights used for averaging across tapers. Only returned if
output='complex'.
Notes
New in version 0.14.0.