mne.time_frequency.csd_tfr#

mne.time_frequency.csd_tfr(epochs_tfr, tmin=None, tmax=None, picks=None, projs=None, verbose=None)[source]#

Compute covariance matrices across frequencies for TFR epochs.

Parameters:

epochs_tfrEpochsTFR: The time-frequency resolved epochs over which to compute the covariance.
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.
picksstr | array_like | slice | None: Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g., ['meg', 'eeg']) will pick channels of those types, channel name strings (e.g., ['MEG0111', 'MEG2623'] will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick good data channels (excluding reference MEG channels). Note that channels in info['bads'] will be included if their names or indices are explicitly provided.
projslist of Projection | None: List of projectors to store in the CSD object. Defaults to None, which means the projectors defined in the EpochsTFR object will be copied.
verbosebool | str | int | None: Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:

resinstance of CrossSpectralDensity: Cross-spectral density restricted to selected channels.

Examples using `mne.time_frequency.csd_tfr`#