mne.time_frequency.psd_multitaper

mne.time_frequency.psd_multitaper(inst, fmin=0, fmax=inf, tmin=None, tmax=None, bandwidth=None, adaptive=False, low_bias=True, normalization=’length’, picks=None, proj=False, n_jobs=1, verbose=None)[source]

Compute the power spectral density (PSD) using multitapers.

Calculates spectral density for orthogonal tapers, then averages them together for each channel/epoch. See [1] for a description of the tapers and [2] for the general method.

Parameters:

inst : instance of Epochs or Raw or Evoked

The data for PSD calculation.

fmin : float

Min frequency of interest

fmax : float

Max frequency of interest

tmin : float | None

Min time of interest

tmax : float | None

Max time of interest

bandwidth : float

The bandwidth of the multi taper windowing function in Hz. The default value is a window half-bandwidth of 4.

adaptive : bool

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

low_bias : bool

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

normalization : str

Either “full” or “length” (default). If “full”, the PSD will be normalized by the sampling rate as well as the length of the signal (as in nitime).

picks : array-like of int | None

The selection of channels to include in the computation. If None, take all channels.

proj : bool

Apply SSP projection vectors. If inst is ndarray this is not used.

n_jobs : int

Number of CPUs to use in the computation.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).
Returns:

psds : ndarray, shape (…, n_freqs)

The power spectral densities. If input is of type Raw, then psds will be shape (n_channels, n_freqs), if input is type Epochs then psds will be shape (n_epochs, n_channels, n_freqs).

freqs : ndarray, shape (n_freqs,)

The frequencies.

See also

mne.io.Raw.plot_psd, mne.Epochs.plot_psd, psd_welch, csd_epochs, psd_array_multitaper

Notes

New in version 0.12.0.

References

[R59]Slepian, D. “Prolate spheroidal wave functions, Fourier analysis, and uncertainty V: The discrete case.” Bell System Technical Journal, vol. 57, 1978.
[R60]Percival D.B. and Walden A.T. “Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques.” Cambridge University Press, 1993.