mne.time_frequency.csd_array_multitaper

mne.time_frequency.csd_array_multitaper(X, sfreq, t0=0, fmin=0, fmax=inf, tmin=None, tmax=None, ch_names=None, n_fft=None, bandwidth=None, adaptive=False, low_bias=True, projs=None, n_jobs=1, verbose=None)[source]

Estimate cross-spectral density from an array using Morlet wavelets.

Parameters
Xarray_like, shape (n_epochs, n_channels, n_times)

The time series data consisting of n_epochs separate observations of signals with n_channels time-series of length n_times.

sfreqfloat

Sampling frequency of observations.

t0float

Time of the first sample relative to the onset of the epoch, in seconds. Defaults to 0.

fminfloat

Minimum frequency of interest, in Hertz.

fmaxfloat | numpy.inf

Maximum frequency of interest, in Hertz.

tminfloat | None

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

tmaxfloat | None

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

ch_nameslist of str | None

A name for each time series. If None (the default), the series will be named ‘SERIES###’.

n_fftint | None

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

bandwidthfloat | None

The bandwidth of the multitaper windowing function in Hz.

adaptivebool

Use adaptive weights to combine the tapered spectra into PSD.

low_biasbool

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

projslist of Projection | None

List of projectors to store in the CSD object. Defaults to None, which means no projectors are stored.

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).

Returns
csdinstance of CrossSpectralDensity

The computed cross-spectral density.