scipy.spatial.distance.cosine¶
- scipy.spatial.distance.cosine(u, v, w=None)[source]¶
Compute the Cosine distance between 1-D arrays.
The Cosine distance between u and v, is defined as
\[1 - \frac{u \cdot v} {||u||_2 ||v||_2}.\]where \(u \cdot v\) is the dot product of \(u\) and \(v\).
- 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
- Returns
- cosinedouble
The Cosine distance between vectors u and v.
Examples
>>> from scipy.spatial import distance >>> distance.cosine([1, 0, 0], [0, 1, 0]) 1.0 >>> distance.cosine([100, 0, 0], [0, 1, 0]) 1.0 >>> distance.cosine([1, 1, 0], [0, 1, 0]) 0.29289321881345254