mne.time_frequency.psd_array_multitaper

mne.time_frequency.psd_array_multitaper(x, sfreq, fmin=0, fmax=inf, bandwidth=None, adaptive=False, low_bias=True, normalization='length', n_jobs=1, verbose=None)

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

Parameters

xarray, shape=(…, n_times)

The data to compute PSD from.

sfreqfloat

The sampling frequency.

fminfloat

The lower frequency of interest.

fmaxfloat

The upper frequency of interest.

bandwidthfloat

The bandwidth of the multi taper windowing function in Hz.

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.

normalizationstr

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).

n_jobsint

The number of jobs to run in parallel (default 1). Requires the joblib package.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

Returns

psdsndarray, shape (…, n_freqs) or

The power spectral densities. All dimensions up to the last will be the same as input.

freqsarray

The frequency points in Hz of the PSD.

See also

mne.io.Raw.plot_psd

mne.Epochs.plot_psd

csd_multitaper

psd_multitaper

Notes

New in version 0.14.0.

Examples using mne.time_frequency.psd_array_multitaper