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