scipy.spatial.distance.seuclidean#

scipy.spatial.distance.seuclidean(u, v, V)[source]#

Return the standardized Euclidean distance between two 1-D arrays.

The standardized Euclidean distance between u and v.

Parameters:
u(N,) array_like

Input array.

v(N,) array_like

Input array.

V(N,) array_like

V is an 1-D array of component variances. It is usually computed among a larger collection vectors.

Returns:
seuclideandouble

The standardized Euclidean distance between vectors u and v.

Examples

>>> from scipy.spatial import distance
>>> distance.seuclidean([1, 0, 0], [0, 1, 0], [0.1, 0.1, 0.1])
4.4721359549995796
>>> distance.seuclidean([1, 0, 0], [0, 1, 0], [1, 0.1, 0.1])
3.3166247903553998
>>> distance.seuclidean([1, 0, 0], [0, 1, 0], [10, 0.1, 0.1])
3.1780497164141406