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 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.

frequencieslist of float

The frequencies of interest, in Hertz.

t0float

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

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_cycles: float | list of float | None

Number of cycles to use when constructing Morlet wavelets. Fixed number or one per frequency. Defaults to 7.

use_fftbool

Whether to use FFT-based convolution to compute the wavelet transform. Defaults to True.

decimint | slice

To reduce memory usage, decimation factor during time-frequency decomposition. Defaults to 1 (no decimation).

If int, uses tfr[…, ::decim]. If slice, uses tfr[…, decim].

projslist 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 be copied.

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.