code: def absolute_distance(x, xp=None, pair=False, dmin=0):
      """pointwise (or pairwise) absolute distance
  
      ``pointwise = |x.T[:,newaxis] - x'.T|  or  pairwise = |x.T - x'.T|.T``
  
      Args:
          x (array): an array of points, ``x``
          xp (array, default=None): a second array of points, ``x'``
          pair (bool, default=False): if True, return the pairwise distances
          dmin (int, default=0): upconvert ``x,x'`` to ``dimension >= dmin``
  
      Returns:
          an array of absolute distances between points
  
      Notes:
          - ``x'==x`` is symmetric with zeros on the diagonal
          - use ``dmin=2`` for the forced upconversion of 1-D arrays"""
      from numpy import abs, asarray, newaxis as nwxs, zeros_like
  
      # cast as arrays of the same dimension
      x = asarray(x)
      xp = x if xp is None else asarray(xp)
      xsize = max(len(x.shape), len(xp.shape), dmin)
      while len(x.shape) < xsize:
          x = x[nwxs]
      while len(xp.shape) < xsize:
          xp = xp[nwxs]
      # prep for build manhattan matrix in single operation
      if pair:
          return abs(x.T - xp.T).T
      xsl = (slice(None),) * xsize + (None,)  # NOTE: [:,:,nwxs] for 2-D
      xpsl = (slice(None),) * max(0, xsize - 1) + (
          None,
      )  # NOTE: [:,nwxs] for 2-D
      return abs(x.T[xsl] - xp.T[xpsl])
  
file_path: mystic/mystic/math/distance.py
label_desc: Use image node_id 2 for calling a global function with example usage: absolute_distance(x, xp, pair, dmin) and returns: abs, abs