scipy.spatial.distance.sqeuclidean¶
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scipy.spatial.distance.sqeuclidean(u, v, w=None)[source]¶ Compute the squared Euclidean distance between two 1-D arrays.
The squared Euclidean distance between u and v is defined as
\[ \begin{align}\begin{aligned}{||u-v||}_2^2\\\left(\sum{(w_i |(u_i - v_i)|^2)}\right)\end{aligned}\end{align} \]- 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
- sqeuclideandouble
The squared Euclidean distance between vectors u and v.
Examples
>>> from scipy.spatial import distance >>> distance.sqeuclidean([1, 0, 0], [0, 1, 0]) 2.0 >>> distance.sqeuclidean([1, 1, 0], [0, 1, 0]) 1.0