scipy.spatial.distance.hamming(u, v, w=None)[source]

Computes the Hamming distance between two 1-D arrays.

The Hamming distance between 1-D arrays u and v, is simply the proportion of disagreeing components in u and v. If u and v are boolean vectors, the Hamming distance is

\[\frac{c_{01} + c_{10}}{n}\]

where \(c_{ij}\) is the number of occurrences of \(\mathtt{u[k]} = i\) and \(\mathtt{v[k]} = j\) for \(k < n\).


u : (N,) array_like

Input array.

v : (N,) array_like

Input array.

w : (N,) array_like, optional

The weights for each value in u and v. Default is None, which gives each value a weight of 1.0


hamming : double

The Hamming distance between vectors u and v.