mne.time_frequency.csd_array_fourier¶

mne.time_frequency.csd_array_fourier(X, sfreq, t0=0, fmin=0, fmax=inf, tmin=None, tmax=None, ch_names=None, n_fft=None, projs=None, n_jobs=1, verbose=None)[source]¶

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

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.
t0float: Time of the first sample relative to the onset of the epoch, in seconds. Defaults to 0.
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.
ch_nameslist of str | None: A name for each time series. If None (the default), the series will be named ‘SERIES###’.
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 no projectors are stored.
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