mahalanobis — SciPy v1.15.3 Manual (original) (raw)

scipy.spatial.distance.

scipy.spatial.distance.mahalanobis(u, v, VI)[source]#

Compute the Mahalanobis distance between two 1-D arrays.

The Mahalanobis distance between 1-D arrays u and v, is defined as

\[\sqrt{ (u-v) V^{-1} (u-v)^T }\]

where V is the covariance matrix. Note that the argument _VI_is the inverse of V.

Parameters:

u(N,) array_like

Input array.

v(N,) array_like

Input array.

VIarray_like

The inverse of the covariance matrix.

Returns:

mahalanobisdouble

The Mahalanobis distance between vectors u and v.

Examples

from scipy.spatial import distance iv = [[1, 0.5, 0.5], [0.5, 1, 0.5], [0.5, 0.5, 1]] distance.mahalanobis([1, 0, 0], [0, 1, 0], iv) 1.0 distance.mahalanobis([0, 2, 0], [0, 1, 0], iv) 1.0 distance.mahalanobis([2, 0, 0], [0, 1, 0], iv) 1.7320508075688772