# scipy.spatial.distance.wminkowski

scipy.spatial.distance.wminkowski(u, v, p, w)

  Compute the weighted Minkowski distance between two 1-D arrays.

  The weighted Minkowski distance between u and v, defined as

  \[\left(\sum{(|w_i (u_i - v_i)|^p)}\right)^{1/p}.\]
  Parameters
    u(N,) array_like

      Input array.

    v(N,) array_like

      Input array.

    p scalar

      The order of the norm of the difference \({||u-v||}_p\).

    w(N,) array_like

      The weight vector.

  Returns
    wminkowski double

      The weighted Minkowski distance between vectors u and v.

  Notes

  `wminkowski` is deprecated and will be removed in SciPy 1.8.0. Use `minkowski` with the `w` argument instead.

  Examples

      >>> from scipy.spatial import distance
      >>> distance.wminkowski([1, 0, 0], [0, 1, 0], 1, np.ones(3))
      2.0
      >>> distance.wminkowski([1, 0, 0], [0, 1, 0], 2, np.ones(3))
      1.4142135623730951
      >>> distance.wminkowski([1, 0, 0], [0, 1, 0], 3, np.ones(3))
      1.2599210498948732
      >>> distance.wminkowski([1, 1, 0], [0, 1, 0], 1, np.ones(3))
      1.0
      >>> distance.wminkowski([1, 1, 0], [0, 1, 0], 2, np.ones(3))
      1.0
      >>> distance.wminkowski([1, 1, 0], [0, 1, 0], 3, np.ones(3))
      1.0

scipy.spatial.distance.sqeuclidean scipy.spatial.distance.dice