mne.time_frequency.csd_array_morlet¶

mne.time_frequency.
csd_array_morlet
(X, sfreq, frequencies, t0=0, tmin=None, tmax=None, ch_names=None, n_cycles=7, use_fft=True, decim=1, 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.
 frequencies
list
offloat
The frequencies of interest, in Hertz.
 t0
float
Time of the first sample relative to the onset of the epoch, in seconds. Defaults to 0.
 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_cycles
float
list
offloat
None
Number of cycles to use when constructing Morlet wavelets. Fixed number or one per frequency. Defaults to 7.
 use_fftbool
Whether to use FFTbased convolution to compute the wavelet transform. Defaults to True.
 decim
int
slice
To reduce memory usage, decimation factor during timefrequency decomposition. Defaults to 1 (no decimation).
 projs
list
ofProjection
None
List of projectors to store in the CSD object. Defaults to
None
, which means the projectors defined in the Epochs object will be copied. 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