code: def scale_0to1(image_in,
                 exclude_outliers_below=False,
                 exclude_outliers_above=False):
      
  
      min_value = image_in.min()
      max_value = image_in.max()
      # making a copy to ensure no side-effects
      image = image_in.copy()
      if exclude_outliers_below:
          perctl = float(exclude_outliers_below)
          image[image < np.percentile(image, perctl)] = min_value
  
      if exclude_outliers_above:
          perctl = float(exclude_outliers_above)
          image[image > np.percentile(image, 100.0 - perctl)] = max_value
  
      image = (image - min_value) / (max_value - min_value)
  
      return image
docs: Scale the two images to [0, 1] based on min/max from both.
  
      Parameters
      -----------
      image_in : ndarray
          Input image
  
      exclude_outliers_{below,above} : float
          Lower/upper limit, a value between 0 and 100.
  
      Returns
      -------
  
      scaled_image : ndarray
          clipped and/or scaled image