mne.time_frequency.csd_multitaper

mne.time_frequency.csd_multitaper(epochs, fmin=0, fmax=inf, tmin=None, tmax=None, picks=None, n_fft=None, bandwidth=None, adaptive=False, low_bias=True, projs=None, n_jobs=1, verbose=None)[source]

Estimate cross-spectral density from epochs using Morlet wavelets.

Parameters:
epochs : instance of Epochs

The epochs to compute the CSD for.

fmin : float | None

Minimum frequency of interest, in Hertz.

fmax : float | np.inf

Maximum frequency of interest, in Hertz.

tmin : float

Minimum time instant to consider, in seconds. If None start at first sample.

tmax : float | None

Maximum time instant to consider, in seconds. If None end at last sample.

picks : list of str | None

The ch_names of the channels to use during CSD computation. Defaults to all good MEG/EEG channels.

n_fft : int | None

Length of the FFT. If None, the exact number of samples between tmin and tmax will be used.

bandwidth : float | None

The bandwidth of the multitaper windowing function in Hz.

adaptive : bool

Use adaptive weights to combine the tapered spectra into PSD.

low_bias : bool

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

projs : list of Projection | None

List of projectors to store in the CSD object. Defaults to None, which means the projectors defined in the Epochs object will by copied.

n_jobs : int

Number of jobs to run in parallel. Defaults to 1.

verbose : bool | str | int | None

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

Returns:
csd : instance of CrossSpectralDensity

The computed cross-spectral density.

Examples using mne.time_frequency.csd_multitaper