spd_learn.functional.mean_cheap#

spd_learn.functional.mean_cheap(X, *, tol=1e-07, maxiter=50, sample_weight=None)[source]#

Cheap mean of SPD/HPD matrices.

Cheap mean is computed as described in [1].

Parameters:

X (ndarray, shape (..., n_matrices, n, n)) – Set of SPD/HPD matrices.
tol (float, default=1e-7) – Tolerance to stop the gradient descent.
maxiter (int, default=50) – Maximum number of iterations.
sample_weight (None | ndarray, shape (n_matrices,), default=None) – Weights for each matrix. If None, it uses equal weights.

Returns:

M – Cheap mean.

Return type:

ndarray, shape (n, n)

Notes

Added in version 0.12.