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 crossspectral 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 timeseries of length n_times.
 sfreq
float
Sampling frequency of observations.
 t0
float
Time of the first sample relative to the onset of the epoch, in seconds. Defaults to 0.
 fmin
float
Minimum frequency of interest, in Hertz.
 fmax
float
numpy.inf
Maximum frequency of interest, in Hertz.
 tmin
float
None
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. ch_names
list
ofstr
None
A name for each time series. If
None
(the default), the series will be named ‘SERIES###’. n_fft
int
None
Length of the FFT. If
None
, the exact number of samples betweentmin
andtmax
will be used. bandwidth
float
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.
 projs
list
ofProjection
None
List of projectors to store in the CSD object. Defaults to
None
, which means no projectors are stored. n_jobs
int
The number of jobs to run in parallel (default 1). Requires the joblib package.
 verbosebool,
str
,int
, orNone
If not None, override default verbose level (see
mne.verbose()
and Logging documentation for more).
 Returns
 csdinstance of
CrossSpectralDensity
The computed crossspectral density.
 csdinstance of