code: def _preprocess_input(test, ref, mask=None):
      
  
      test = np.abs(np.copy(test)).astype('float64')
      ref = np.abs(np.copy(ref)).astype('float64')
      test = min_max_normalize(test)
      ref = min_max_normalize(ref)
  
      if (not isinstance(mask, np.ndarray)) and (mask is not None):
          raise ValueError("mask should be None, or a np.ndarray,"
                           " got '{0}' instead.".format(mask))
  
      if mask is None:
          return test, ref, None
  
      return test, ref, mask
docs: Wrapper to the metric
  
      Parameters
      ----------
      ref : np.ndarray
          the reference image
      test : np.ndarray
          the tested image
      mask : np.ndarray, optional
          the mask for the ROI
  
      Notes
      -----
      Compute the metric only on magnetude.
  
      Returns
      -------
      ssim: float, the snr