code: def _data_zeroed(self):
          
  
          # NOTE: using np.where is faster than
          #     _data = np.copy(self.data_cutout)
          #     self._data[self._total_mask] = 0.
          return np.where(self._total_mask, 0,
                          self.data_cutout).astype(np.float64)
docs: A 2D `~numpy.nddarray` cutout from the input ``data`` where any
          masked pixels (_segment_mask, _input_mask, or _data_mask) are
          set to zero.  Invalid values (e.g. NaNs or infs) are set to
          zero.  Units are dropped on the input ``data``.