# scipy.spatial.distance.euclidean

scipy.spatial.distance.euclidean(u, v, w=None)

  Computes the Euclidean distance between two 1-D arrays.

  The Euclidean distance between 1-D arrays u and v, is defined as

  \[ \begin{align}\begin{aligned}{||u-v||}_2\\\left(\sum{(w_i |(u_i - v_i)|^2)}\right)^{1/2}\end{aligned}\end{align} \]
  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
    euclidean double

      The Euclidean distance between vectors u and v.

  Examples

      >>> from scipy.spatial import distance
      >>> distance.euclidean([1, 0, 0], [0, 1, 0])
      1.4142135623730951
      >>> distance.euclidean([1, 1, 0], [0, 1, 0])
      1.0

scipy.spatial.distance.cosine scipy.spatial.distance.jensenshannon