`scipy.spatial.distance:sokalsneath`

source: /scipy/spatial/distance.py:1515

Signature

def sokalsneath(u, v, w = None)

Summary

Compute the Sokal-Sneath dissimilarity between two boolean 1-D arrays.

Extended Summary

The Sokal-Sneath dissimilarity between u and v,

\frac{R}{c _{T T} + R}

where $c_{ij}$ is the number of occurrences of $u [k] = i$ and $v [k] = j$ for $k < n$ and $R = 2 (c_{T F} + c_{F T})$ .

Parameters

u : (N,) array_like, bool: Input array.
v : (N,) array_like, bool: 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

sokalsneath : double: The Sokal-Sneath dissimilarity between vectors u and v.

Examples

from scipy.spatial import distance

✓

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

✗

np.float64(-2.0)

Aliases

scipy.spatial.distance.sokalsneath