papyri
{ } Raw JSON

bundles / scipy 1.17.1 / scipy / spatial / distance / hamming

function

scipy.spatial.distance:hamming

source: /scipy/spatial/distance.py :720

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

where is the number of occurrences of and for .

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])
✗

Aliases

  • scipy.spatial.distance.hamming

Referenced by

This package