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)[source]¶

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). If -1, it is set to the number of CPU cores. Requires the joblib package.
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: 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.