code: def sokalsneath(u, v, w=None):
      """
      Compute the Sokal-Sneath dissimilarity between two boolean 1-D arrays.
  
      The Sokal-Sneath dissimilarity between `u` and `v`,
  
      .. math::
  
         \\frac{R}
              {c_{TT} + R}
  
      where :math:`c_{ij}` is the number of occurrences of
      :math:`\\mathtt{u[k]} = i` and :math:`\\mathtt{v[k]} = j` for
      :math:`k < n` and :math:`R = 2(c_{TF} + c_{FT})`.
  
      Parameters
      ----------
      u : (N,) array_like, bool
          Input array.
      v : (N,) array_like, bool
          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
      -------
      sokalsneath : double
          The Sokal-Sneath dissimilarity between vectors `u` and `v`.
  
      Examples
      --------
      >>> from scipy.spatial import distance
      >>> distance.sokalsneath([1, 0, 0], [0, 1, 0])
      1.0
      >>> distance.sokalsneath([1, 0, 0], [1, 1, 0])
      0.66666666666666663
      >>> distance.sokalsneath([1, 0, 0], [2, 1, 0])
      0.0
      >>> distance.sokalsneath([1, 0, 0], [3, 1, 0])
      -2.0
  
      """
      u = _validate_vector(u)
      v = _validate_vector(v)
      if u.dtype == v.dtype == bool and w is None:
          ntt = (u & v).sum()
      elif w is None:
          ntt = (u * v).sum()
      else:
          w = _validate_weights(w)
          ntt = (u * v * w).sum()
      (nft, ntf) = _nbool_correspond_ft_tf(u, v, w=w)
      denom = np.array(ntt + 2.0 * (ntf + nft))
      if not denom.any():
          raise ValueError(
              "Sokal-Sneath dissimilarity is not defined for "
              "vectors that are entirely false."
          )
      return float(2.0 * (ntf + nft)) / denom
  
imports: import math
  import warnings
  import numpy
  import dataclasses
  from typing import Optional, Callable
  from functools import partial
  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
  from .None import _distance_pybind
label_desc: Use image node_id 37 for calling a global function with example usage: sokalsneath(u, v, w) and returns: unknown