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 :

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.

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