code: def tas(img):
      """
      values = tas(img)
  
      Compute Threshold Adjacency Statistics
  
      TAS were presented by Hamilton et al.  in "Fast automated cell phenotype
      image classification" (https://www.biomedcentral.com/1471-2105/8/110)
  
      Also returns a version computed on the negative of the binarisation defined
      by Hamilton et al.
  
      See also pftas() for a variation without any hardcoded parameters.
  
      Parameters
      ----------
      img : ndarray, 2D or 3D
          input image
  
      Returns
      -------
      values : ndarray
          A 1-D ndarray of feature values
  
      See Also
      --------
      pftas : Parameter free TAS
      """
      return _tas(img, 30, 30)
  
imports: import numpy
  from ..convolve import convolve
  from ..thresholding import otsu
label_desc: Use image node_id 2 for calling a global function with example usage: tas(img) and returns: _tas