# 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.

fmax

Maximum frequency of interest, in Hertz.

tmin

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

tmax

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

ch_names

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

n_fft

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

bandwidth

The bandwidth of the multitaper windowing function in Hz.

Use adaptive weights to combine the tapered spectra into PSD.

low_biasbool

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

projs

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.

verbose

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

Returns
csdinstance of CrossSpectralDensity

The computed cross-spectral density.