pyriemann.utils.distance.distance¶
- pyriemann.utils.distance.distance(A, B, metric='riemann', squared=False)¶
Distance between matrices according to a metric.
Compute the distance between two matrices A and B according to a metric [1], or between a set of matrices A and another matrix B.
- Parameters:
- Andarray, shape (n, n) or shape (n_matrices, n, n)
First matrix, or set of matrices.
- Bndarray, shape (n, n)
Second matrix.
- metricstring | callable, default=”riemann”
Metric for distance, can be: “chol”, “euclid”, “harmonic”, “kullback”, “kullback_right”, “kullback_sym”, “logchol”, “logdet”, “logeuclid”, “riemann”, “wasserstein”, or a callable function.
- squaredbool, default False
Return squared distance.
Added in version 0.5.
- Returns:
- dfloat or ndarray, shape (n_matrices, 1)
Distance between A and B.
References
[1]Review of Riemannian distances and divergences, applied to SSVEP-based BCI S. Chevallier, E. K. Kalunga, Q. Barthélemy, E. Monacelli. Neuroinformatics, Springer, 2021, 19 (1), pp.93-106