scipy.spatial.distance.

yule#

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

Compute the Yule dissimilarity between two boolean 1-D arrays.

The Yule dissimilarity is defined as

\frac{R}{c_{T T} * c_{F F} + \frac{R}{2}}

$\frac{R}{c_{TT} * c_{FF} + \frac{R}{2}}$

where $c_{ij}$ is the number of occurrences of $\mathtt{u[k]} = i$ and $\mathtt{v[k]} = j$ for $k < n$ and $R = 2.0 * c_{TF} * c_{FT}$ .

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:

Examples

>>> from scipy.spatial import distance
>>> distance.yule([1, 0, 0], [0, 1, 0])
2.0
>>> distance.yule([1, 1, 0], [0, 1, 0])
0.0