`scipy.spatial.distance._distance:hamming`

source: build-install/usr/lib/python3.14/site-packages/scipy/spatial/distance/_distance.py:650

Signature

def hamming(u, v, w = None)

Summary

Compute the Hamming distance between two 1-D arrays.

Extended Summary

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 $u [k] = i$ and $v [k] = j$ for $k < n$ .

Parameters

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

Returns

hamming : double: The Hamming distance between vectors u and v.

Examples

from scipy.spatial import distance

✓

distance.hamming([1, 0, 0], [0, 1, 0])
distance.hamming([1, 0, 0], [1, 1, 0])
distance.hamming([1, 0, 0], [2, 0, 0])
distance.hamming([1, 0, 0], [3, 0, 0])

✗

np.float64(0.3333333333333333)