code: def mask_and_dates_for_term(self,
                                  term,
                                  root_mask_term,
                                  workspace,
                                  all_dates):
          
          mask = term.mask
          mask_offset = self.extra_rows[mask] - self.extra_rows[term]
  
          # This offset is computed against root_mask_term because that is what
          # determines the shape of the top-level dates array.
          dates_offset = (
              self.extra_rows[root_mask_term] - self.extra_rows[term]
          )
  
          return workspace[mask][mask_offset:], all_dates[dates_offset:]
docs: Load mask and mask row labels for term.
  
          Parameters
          ----------
          term : Term
              The term to load the mask and labels for.
          root_mask_term : Term
              The term that represents the root asset exists mask.
          workspace : dict[Term, any]
              The values that have been computed for each term.
          all_dates : pd.DatetimeIndex
              All of the dates that are being computed for in the pipeline.
  
          Returns
          -------
          mask : np.ndarray
              The correct mask for this term.
          dates : np.ndarray
              The slice of dates for this term.