code: def ccs_normalize(compIM, ccsnorm):
      
      compIM = np.asarray(compIM)
      ccsnorm = np.asarray(ccsnorm)
      ys = ccsnorm.shape[0]
      xs = ccsnorm.shape[1]
      # start with first column
      ccsnorm[2::2, 0] = ccsnorm[1:ys - 1:2, 0]
      # continue with middle columns
      ccsnorm[:, 2::2] = ccsnorm[:, 1:xs - 1:2]
      # finish whith last row if even
      if xs % 2 is 0:
          ccsnorm[2::2, xs - 1] = ccsnorm[1:ys - 1:2, xs - 1]
      # solve problem with 0/0
      ccsnorm[ccsnorm == 0] = np.nextafter(0., 1., dtype = ccsnorm.dtype)
  
      res = compIM / ccsnorm
      return res
docs: normalize the ccs representation
  
      Parameters
      ----------
      compIM: 2d array
          The CCS image in CCS representation
      ccsnorm: 2d array
          The normalization matrix in ccs representation
  
      Returns
      -------
      compIM: 2d array
          The normalized CCS image
  
      Notes
      -----
      (basically an element wise division for CCS)
      Should probably not be used from outside