mne_features.bivariate.compute_time_corr¶

mne_features.bivariate.compute_time_corr(data, with_eigenvalues=True, include_diag=False)¶

Correlation Coefficients (computed in the time domain).

Parameters

datandarray, shape (n_channels, n_times)

The signals.

with_eigenvaluesbool (default: True)

If True, the function also returns the eigenvalues of the correlation matrix.

include_diagbool (default: False)

If False, features corresponding to pairs of identical electrodes are not computed. In other words, features are not computed from pairs of electrodes of the form (ch[i], ch[i]).

Returns

outputndarray, shape (n_output,)

With n_output = n_coefs + n_channels if with_eigenvalues is True and n_output = n_coefs if with_eigenvalues is False. If include_diag is True, then n_coefs = n_channels * (n_channels + 1) // 2 and n_coefs = n_channels * (n_channels - 1) // 2 otherwise.

Notes

Alias of the feature function: time_corr. See [1].

References

1

https://kaggle2.blob.core.windows.net/forum-message-attachments/ 134445/4803/seizure-detection.pdf