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 of floats: Input array.

Deprecated since version 1.15.0: Complex u is deprecated and will raise an error in SciPy 1.17.0
v(N,) array_like of floats: Input array.

Deprecated since version 1.15.0: Complex v is deprecated and will raise an error in SciPy 1.17.0
w(N,) array_like of floats, 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