mahalanobis(u, v, VI)
The Mahalanobis distance between 1-D arrays u and v, is defined as
where V
is the covariance matrix. Note that the argument :None:None:`VI` is the inverse of V
.
Input array.
Input array.
The inverse of the covariance matrix.
Compute the Mahalanobis distance between two 1-D arrays.
>>> 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) 1.7320508075688772See :
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.spatial.distance.mahalanobis
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