spd_learn.functional.norm#

spd_learn.functional.norm(X, Cref, metric='riemann')[source]#

Norm according to a specified metric.

It calculates the norm of the matrix \(\mathbf{X}\) in the tangent space at \(\mathbf{C}_\text{ref}\), according to a specified metric.

Parameters:

X (ndarray, shape (..., n, n)) – Matrices in the tangent space at Cref.
Cref (ndarray, shape (n, n) | None) – Reference matrix.
metric (string | callable, default="riemann") – Metric used for norm, can be: “euclid”, “logeuclid”, “riemann”, or a callable function.

Returns:

N – Norm of X.

Return type:

float or ndarray, shape (…,)

Notes

Added in version 0.11.

Changed in version 0.12: Add support for NumPy and PyTorch.