coffeine.covariance_transformers.NaiveVec

class coffeine.covariance_transformers.NaiveVec(method, return_data_frame=True)

Vectorize SPD matrix by flattening the upper triangle.

Upper “naive” vectorization as described in [1].

Parameters:

metricstr, default=’riemann’

The Riemannian metric to use. See PyRiemann documentation for details and valid choices.

return_data_framebool, default=True

Returning the result in a pandas data frame or not.

References

[1]

D. Sabbagh, P. Ablin, G. Varoquaux, A. Gramfort, and D.A. Engemann. Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states. NeuroImage, page 116893,2020. ISSN 1053-8119. https://doi.org/10.1016/j.neuroimage.2020.116893