pyriemann.utils.distance.distance_euclid¶
- pyriemann.utils.distance.distance_euclid(A, B, squared=False)¶
Euclidean distance between matrices.
The Euclidean distance between two matrices \(\mathbf{A}\) and \(\mathbf{B}\) is defined as the Frobenius norm of the difference of the two matrices:
\[d(\mathbf{A},\mathbf{B}) = \Vert \mathbf{A} - \mathbf{B} \Vert_F\]- Parameters:
- Andarray, shape (…, n, m)
First matrices, at least 2D ndarray.
- Bndarray, shape (…, n, m)
Second matrices, same dimensions as A.
- squaredbool, default False
Return squared distance.
New in version 0.5.
- Returns:
- dfloat or ndarray, shape (…,)
Euclidean distance between A and B.
See also