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scipy.spatial.distance.

# euclidean

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

  Computes the Euclidean distance between two arrays.

  The Euclidean distance between 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 float or ndarray

      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