code: def correlation(u, v):
      """Compute the correlation distance between two 1-D arrays.
  
      The correlation distance is defined as
  
      .. math::
          d(u, v) = 1 - \\frac{(u - \\bar{u}) \\cdot (v - \\bar{v})}{
          \\|(u - \\bar{u})\\|_2 \\|(v - \\bar{v})\\|_2}
  
      where :math:`\\bar{u}` is the mean of the elements of :math:`u` and
      :math:`x \\cdot y` is the dot product.
  
      Args:
          u (array_like): Input array of size (N,)
          v (array_like): Input array of size (N,)
  
      Returns:
          correlation (double): The correlation distance between
          vectors `u` and `v`.
      """
      if not pylibraft_available:
          raise RuntimeError("pylibraft is not installed")
      u = cupy.asarray(u)
      v = cupy.asarray(v)
      output_arr = cupy.zeros((1,), dtype=u.dtype)
      pairwise_distance(u, v, output_arr, "correlation")
  
      return output_arr[0]
  
imports: import cupy
label_desc: Use image node_id 7 for calling a global function with example usage: correlation(u, v) and returns: output_arr