scipy.spatial.distance.mahalanobis¶

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

Computes 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 :

Parameters :	u : (N,) array_like Input array. v : (N,) array_like Input array. VI : ndarray The inverse of the covariance matrix.
Returns :	mahalanobis : double The Mahalanobis distance between vectors u and v.

u : (N,) array_like

Input array.

v : (N,) array_like

Input array.

VI : ndarray

The inverse of the covariance matrix.

Returns :

mahalanobis : double

The Mahalanobis distance between vectors u and v.