pyriemann.geometry.mean.mean_poweuclid¶
- pyriemann.geometry.mean.mean_poweuclid(X, p, *, sample_weight=None, **kwargs)[source]¶
Mean of SPD/HPD matrices according to the power Euclidean metric.
Power Euclidean mean of order \(p\) is [1]:
\[\mathbf{M} = \left( \sum_i w_i \ \mathbf{X}_i^p \right)^{1/p}\]with \(w\) being the weights which sum to 1.
- Parameters:
- Xndarray, shape (…, n_matrices, n, n)
Set of SPD/HPD matrices.
- pfloat
Exponent.
- sample_weightNone | ndarray, shape (n_matrices,), default=None
Weights for each matrix. If None, it uses equal weights.
- Returns:
- Mndarray, shape (…, n, n)
Power Euclidean mean.
See also
Notes
Changed in version 0.12: Add support for NumPy and PyTorch.
References
[1]Power Euclidean metrics for covariance matrices with application to diffusion tensor imaging I.L. Dryden, X. Pennec, & J.M. Peyrat. arXiv, 2010.