`scipy.spatial.distance:mahalanobis`

Signature

def mahalanobis(u, v, VI)

Compute the Mahalanobis distance between two 1-D arrays.

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

(u - v) V^{- 1} (u - v)^{T}

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

mahalanobis : double: The Mahalanobis distance between vectors u and v.

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)
distance.mahalanobis([0, 2, 0], [0, 1, 0], iv)
distance.mahalanobis([2, 0, 0], [0, 1, 0], iv)

✗

np.float64(1.7320508075688772)