pyeeg.preprocess.covariance

pyeeg.preprocess.covariance(X, estimator='cov')

Estimation of one covariance matrix on the whole dataset. If X is of shape (trials, samples, channels) Will concatenate all trials together to compute a single covariance matrix across all of them.

Parameters:

• X (ndarray (nsamples, nchannels) or (ntrials, nsamples, nchannels)) – Input data. If 3d, all trials are concatenated along the sample dimension before estimating the covariance.

• estimator (str or callable) – One of the covariance estimators understood by _check_est() ('cov', 'scm', 'lwf', 'oas', 'mcd', 'corr') or a callable returning a covariance matrix.

Returns:

C – The estimated covariance matrix.

Return type:

ndarray (nchannels, nchannels)