code: def masked_clip_2d(data, mask, lower, upper):
      """
      Clip the elements of an input array between lower and upper bounds,
      skipping over elements that are masked out.
  
      Parameters
      ----------
      data: np.ndarray
          Numeric ndarray that will be clipped in-place
      mask: np.ndarray
          Boolean ndarray where True values indicate elements that should be
          skipped
      lower: int or float
          Lower bound to clip to
      upper: int or float
          Upper bound to clip to
  
      Returns
      -------
      None
          data array is modified in-place
      """
      for i in range(data.shape[0]):
          for j in range(data.shape[1]):
              if mask[i, j]:
                  continue
              val = data[i, j]
              if val < lower:
                  data[i, j] = lower
              elif val > upper:
                  data[i, j] = upper
  
label_desc: Use image node_id 1 for calling a global function with example usage: masked_clip_2d(data, mask, lower, upper) without return types