code: def _test_price_rounding(self, frequency, field):
      equity = self.asset_finder.retrieve_asset(2)
      future = self.asset_finder.retrieve_asset(10001)
      cf = self.data_portal.asset_finder.create_continuous_future(
          "BUZ",
          0,
          "calendar",
          None,
      )
      minutes = self.nyse_calendar.minutes_for_session(
          self.trading_days[0]
      )
  
      if frequency == "1m":
          minute = minutes[0]
          expected_equity_volume = 100
          expected_future_volume = 100
          data_frequency = "minute"
      else:
          minute = minutes[0].normalize()
          expected_equity_volume = 100 * US_EQUITIES_MINUTES_PER_DAY
          expected_future_volume = 100 * FUTURES_MINUTES_PER_DAY
          data_frequency = "daily"
  
      # Equity prices should be floored to three decimal places.
      expected_equity_values = {
          "open": 1.005,
          "high": 1.005,
          "low": 1.005,
          "close": 1.005,
          "volume": expected_equity_volume,
      }
      # Futures prices should be rounded to four decimal places.
      expected_future_values = {
          "open": 1.0055,
          "high": 1.0059,
          "low": 1.0051,
          "close": 1.0055,
          "volume": expected_future_volume,
      }
  
      result = self.data_portal.get_history_window(
          assets=[equity, future, cf],
          end_dt=minute,
          bar_count=1,
          frequency=frequency,
          field=field,
          data_frequency=data_frequency,
      )
      expected_result = pd.DataFrame(
          {
              equity: expected_equity_values[field],
              future: expected_future_values[field],
              cf: expected_future_values[field],
          },
          index=[minute],
          dtype=float64_dtype,
      )
  
      assert_equal(result, expected_result)
  
imports: from collections import OrderedDict
  from numpy import array, append, nan, full
  from numpy.testing import assert_almost_equal
  import pandas
  from pandas.tslib import Timedelta
  from catalyst.assets import Equity, Future
  from catalyst.data.data_portal import HISTORY_FREQUENCIES, OHLCV_FIELDS
  from catalyst.data.minute_bars import FUTURES_MINUTES_PER_DAY, US_EQUITIES_MINUTES_PER_DAY
  from catalyst.testing import parameter_space
  from catalyst.testing.fixtures import CatalystTestCase, WithTradingSessions, WithDataPortal, alias
  from catalyst.testing.predicates import assert_equal
  from catalyst.utils.numpy_utils import float64_dtype
label_desc: Use image node_id 14 for calling the DataPortalTestBase obj's underlying member method code with example usage: obj._test_price_rounding(frequency, field) without return types