# scipy.spatial.distance.correlation¶

scipy.spatial.distance.correlation(u, v, w=None, centered=True)[source]

Compute the correlation distance between two 1-D arrays.

The correlation distance between u and v, is defined as

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

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

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 correlation : double The correlation distance between 1-D array u and v.

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