spd_learn.functional.geodesic_wasserstein#
- spd_learn.functional.geodesic_wasserstein(A, B, alpha=0.5)[source]#
Wasserstein geodesic between SPD/HPD matrices.
The matrix at position \(\alpha\) on the Wasserstein geodesic between two SPD/HPD matrices \(\mathbf{A}\) and \(\mathbf{B}\) is given in [1]:
\[\mathbf{C} = (1-\alpha)^2\mathbf{A} + \alpha^2\mathbf{B} + \alpha(1-\alpha)((\mathbf{AB})^{1/2} + (\mathbf{BA})^{1/2})\]\(\mathbf{C}\) is equal to \(\mathbf{A}\) if \(\alpha\) = 0, and \(\mathbf{B}\) if \(\alpha\) = 1.
- Parameters:
A (ndarray, shape (..., n, n)) – First SPD/HPD matrices.
B (ndarray, shape (..., n, n)) – Second SPD/HPD matrices.
alpha (float | ndarray, shape (...,), default=0.5) –
Position on the geodesic. If ndarray, one value per matrix pair.
Changed in version 0.12.
- Returns:
C – SPD/HPD matrices on the Wasserstein geodesic.
- Return type:
ndarray, shape (…, n, n)
Notes
Added in version 0.8.
Changed in version 0.12: Add support for NumPy and PyTorch. Add support for array-valued alpha.
See also
References
[1]Wasserstein Riemannian geometry of Gaussian densities L. Malagò, L. Montrucchio, G. Pistone. Information Geometry, 2018, 1, pp. 137–179.