pyriemann.utils.mean.mean_logeuclid¶
- pyriemann.utils.mean.mean_logeuclid(covmats, sample_weight=None)¶
Mean of SPD/HPD matrices according to the log-Euclidean metric.
Log-Euclidean mean is [1]:
\[\mathbf{C} = \exp{ \left( \sum_i w_i \ \log{\mathbf{X}_i} \right) }\]- Parameters:
- covmatsndarray, shape (n_matrices, n, n)
Set of SPD/HPD matrices.
- sample_weightNone | ndarray, shape (n_matrices,), default=None
Weights for each matrix. If None, it uses equal weights.
- Returns:
- Cndarray, shape (n, n)
Log-Euclidean mean.
See also
References
[1]Geometric means in a novel vector space structure on symmetric positive-definite matrices V. Arsigny, P. Fillard, X. Pennec, and N. Ayache. SIAM Journal on Matrix Analysis and Applications. Volume 29, Issue 1 (2007).