code: def 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
  
      .. math::
  
         {||u-v||}_2
  
         \\left(\\sum{(w_i |(u_i - v_i)|^2)}\\right)^{1/2}
  
      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
  
      """
      return minkowski(u, v, p=2, w=w)
  
imports: from __future__ import division, print_function, absolute_import
  import warnings
  import numpy
  from functools import partial
  from collections import namedtuple
  from scipy._lib.six import callable, string_types
  from scipy._lib.six import xrange
  from scipy._lib._util import _asarray_validated
  from .None import _distance_wrap
  from .None import _hausdorff
  from ..linalg import norm
  from ..special import rel_entr
label_desc: Use image node_id 20 for calling a global function with example usage: euclidean(u, v, w) and returns: minkowski