code: def test_quantiles_are_computed_correctly():
      for _ in range(5):
          data = np.random.random_integers(0, 1000, 100_000).tolist()
          a = round(random.uniform(0, 1), 2)
          b = round(random.uniform(a, 1), 2)
          a, b = min(a, b), max(a, b)
  
          df_quantile = compute_quantile_df(data, a, b)
  
          first = df_quantile[
              df_quantile["data_type"]
              == f"first {int(a * 100)}% quantile"
          ]
          last = df_quantile[
              df_quantile["data_type"]
              == f"last {100 - int(b * 100)}% quantile"
          ]
          sorted_data = sorted(data)
          # use -1 and +1 to account for rounding errors
          expected_first_quantile_range = sorted_data[
              int(len(sorted_data) * a)
              - 1 : int(len(sorted_data) * a)
              + 1
          ]
          expected_last_quantile_range = sorted_data[
              -int(len(sorted_data) * (1 - b))
              - 1 : -int(len(sorted_data) * (1 - b))
              + 1
          ]
  
          assert first.iloc[-1][0] in expected_first_quantile_range
          assert last.iloc[0][0] in expected_last_quantile_range
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_quantiles_are_computed_correctly() without return types