mne.time_frequency.psd_array_multitaper#

mne.time_frequency.psd_array_multitaper(x, sfreq, fmin=0.0, fmax=inf, bandwidth=None, adaptive=False, low_bias=True, normalization='length', output='power', n_jobs=None, *, max_iter=150, verbose=None)[source]#

Compute power spectral density (PSD) using a multi-taper method.

The power spectral density is computed with DPSS tapers[1].

Parameters:

xarray, shape=(…, n_times)

The data to compute PSD from.

sfreqfloat

The sampling frequency.

fmin, fmaxfloat

The lower- and upper-bound on frequencies of interest. Default is fmin=0, fmax=np.inf (spans all frequencies present in the data).

bandwidthfloat

Half-bandwidth of the multi-taper window function in Hz. For a given frequency, frequencies at ± half-bandwidth are smoothed together. The default value is a half-bandwidth of 4.

adaptivebool

Use adaptive weights to combine the tapered spectra into PSD (slow, use n_jobs >> 1 to speed up computation).

low_biasbool

Only use tapers with more than 90% spectral concentration within bandwidth.

normalization‘full’ | ‘length’

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'.

outputstr

The format of the returned psds array, 'complex' or 'power':

'power' : the power spectral density is returned.
'complex' : the complex fourier coefficients are returned per taper.

n_jobsint | None

The 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.

max_iterint

Maximum number of iterations to reach convergence when combining the tapered spectra with adaptive weights (see argument adaptive). This argument has not effect if adaptive is set to False.

verbosebool | str | int | None

Control 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.

Returns:

psdsndarray, 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.
freqsarray: The frequency points in Hz of the PSD.
weightsndarray: The weights used for averaging across tapers. Only returned if output='complex'.