`scipy.spatial.distance:chebyshev`

source: /scipy/spatial/distance.py :1041

Signature

def chebyshev ( u , v , w = None )

Summary

Compute the Chebyshev distance.

Extended Summary

The Chebyshev distance between real vectors $u \equiv (u_{1}, \dots, u_{n})$ and $v \equiv (v_{1}, \dots, v_{n})$ is defined as ^[1]

d_{chebyshev} (u, v) := 1 \leq i \leq n max ∣ u_{i} - v_{i} ∣

If a (non-negative) weight vector $w \equiv (w_{1}, \dots, w_{n})$ is supplied, the weighted Chebyshev distance is defined to be the weighted Minkowski distance of infinite order; that is,

d_{chebyshev} (u, v; w) := p \to \infty lim (i = 1 \sum n w_{i} ∣ u_{i} - v_{i} ∣^{p})^{\frac{1}{p}} = 1 \leq i \leq n max 1_{w_{i} > 0} ∣ u_{i} - v_{i} ∣

Parameters

u : (N,) array_like of floats: Input vector.
v : (N,) array_like of floats: Input vector.
w : (N,) array_like of floats, optional: Weight vector. Default is None, which gives all pairs $(u_{i}, v_{i})$ the same weight 1.0.

Returns

chebyshev : float: The Chebyshev distance between vectors u and v, optionally weighted by w.

Examples

from scipy.spatial import distance

✓

distance.chebyshev([1, 0, 0], [0, 1, 0])
distance.chebyshev([1, 1, 0], [0, 1, 0])

✗

Aliases

scipy.spatial.distance.chebyshev