code: def test_overnight_adjustments(self):
      # Should incorporate adjustments on midnight 01/06
      current_dt = pd.Timestamp("2015-01-06 8:45", tz="US/Eastern")
      bar_data = self.create_bardata(
          lambda: current_dt,
      )
  
      adj_expected = {
          "open": np.arange(8381, 8391) / 4.0,
          "high": np.arange(8382, 8392) / 4.0,
          "low": np.arange(8379, 8389) / 4.0,
          "close": np.arange(8380, 8390) / 4.0,
          "volume": np.arange(8380, 8390) * 100 * 4.0,
          "price": np.arange(8380, 8390) / 4.0,
      }
  
      expected = {
          "open": np.arange(383, 393) / 2.0,
          "high": np.arange(384, 394) / 2.0,
          "low": np.arange(381, 391) / 2.0,
          "close": np.arange(382, 392) / 2.0,
          "volume": np.arange(382, 392) * 100 * 2.0,
          "price": np.arange(382, 392) / 2.0,
      }
  
      # Use a window looking back to 3:51pm from 8:45am the following day.
      # This contains the last ten minutes of the equity session for
      # 2015-01-05.
      window_start = pd.Timestamp("2015-01-05 20:51", tz="UTC")
      window_end = pd.Timestamp("2015-01-06 13:44", tz="UTC")
      window_length = len(
          self.trading_calendar.minutes_in_range(
              window_start, window_end
          )
      )
  
      with handle_non_market_minutes(bar_data):
          # Single field, single asset
          for field in ALL_FIELDS:
              values = bar_data.history(
                  self.SPLIT_ASSET,
                  field,
                  window_length,
                  "1m",
              )
  
              # The first 10 bars the `values` correspond to the last
              # 10 minutes in the 2015-01-05 session.
              np.testing.assert_array_equal(
                  values.values[:10], adj_expected[field], err_msg=field
              )
  
          # Multi field, single asset
          values = bar_data.history(
              self.SPLIT_ASSET, ["open", "volume"], window_length, "1m"
          )
          np.testing.assert_array_equal(
              values.open.values[:10], adj_expected["open"]
          )
          np.testing.assert_array_equal(
              values.volume.values[:10], adj_expected["volume"]
          )
  
          # Single field, multi asset
          values = bar_data.history(
              [self.SPLIT_ASSET, self.ASSET2],
              "open",
              window_length,
              "1m",
          )
          np.testing.assert_array_equal(
              values[self.SPLIT_ASSET].values[:10], adj_expected["open"]
          )
          np.testing.assert_array_equal(
              values[self.ASSET2].values[:10], expected["open"] * 2
          )
  
          # Multi field, multi asset
          values = bar_data.history(
              [self.SPLIT_ASSET, self.ASSET2],
              ["open", "volume"],
              window_length,
              "1m",
          )
          np.testing.assert_array_equal(
              values.open[self.SPLIT_ASSET].values[:10],
              adj_expected["open"],
          )
          np.testing.assert_array_equal(
              values.volume[self.SPLIT_ASSET].values[:10],
              adj_expected["volume"],
          )
          np.testing.assert_array_equal(
              values.open[self.ASSET2].values[:10], expected["open"] * 2
          )
          np.testing.assert_array_equal(
              values.volume[self.ASSET2].values[:10],
              expected["volume"] / 2,
          )
  
imports: from textwrap import dedent
  from nose_parameterized import parameterized
  import numpy
  from numpy import nan
  import pandas
  from six import iteritems
  from catalyst import TradingAlgorithm
  from catalyst._protocol import handle_non_market_minutes, BarData
  from catalyst.assets import Asset, Equity
  from catalyst.errors import HistoryInInitialize, HistoryWindowStartsBeforeData
  from catalyst.finance.trading import SimulationParameters
  from catalyst.finance.asset_restrictions import NoRestrictions
  from catalyst.testing import create_minute_df_for_asset, str_to_seconds, MockDailyBarReader
  from catalyst.testing.fixtures import WithCreateBarData, WithDataPortal, CatalystTestCase, alias
label_desc: Use image node_id 13 for calling the MinuteEquityHistoryTestCase obj's underlying member method code with example usage: obj.test_overnight_adjustments() without return types