mne.time_frequency.csd_fourier

mne.time_frequency.csd_fourier(epochs, fmin=0, fmax=inf, tmin=None, tmax=None, picks=None, n_fft=None, projs=None, n_jobs=1, verbose=None)[source]

Estimate cross-spectral density from an array using short-time fourier.

Parameters
epochsinstance of Epochs

The epochs to compute the CSD for.

fminfloat

Minimum frequency of interest, in Hertz.

fmaxfloat | numpy.inf

Maximum frequency of interest, in Hertz.

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 | list | 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).

n_fftint | None

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

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 by 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). If used, it should be passed as a keyword-argument only.

Returns
csdinstance of CrossSpectralDensity

The computed cross-spectral density.