# cupyx.scipy.spatial.distance.correlation#

cupyx.scipy.spatial.distance.correlation(u, v)[source]#

Compute the correlation distance between two 1-D arrays.

The correlation distance is defined as

$d(u, v) = 1 - \frac{(u - \bar{u}) \cdot (v - \bar{v})}{ \|(u - \bar{u})\|_2 \|(v - \bar{v})\|_2}$

where $$\bar{u}$$ is the mean of the elements of $$u$$ and $$x \cdot y$$ is the dot product.

Parameters
• u (array_like) – Input array of size (N,)

• v (array_like) – Input array of size (N,)

Returns

The correlation distance between vectors u and v.

Return type

correlation (double)