code: def _test_low_transaction_volume(self):
      # With a volume limit of 0.001, and a bar volume of 100, we should
      # compute a transaction volume of 100 * 0.001 = 0.1, which gets rounded
      # down to zero. In this case we expect no amount to be transacted.
      model = VolatilityVolumeShare(volume_limit=0.001)
  
      minute = pd.Timestamp("2006-03-01 11:35AM", tz="UTC")
      data = self.create_bardata(simulation_dt_func=lambda: minute)
      order = Order(dt=data.current_dt, asset=self.ASSET, amount=10)
      price, amount = model.process_order(data, order)
  
      self.assertIsNone(price)
      self.assertIsNone(amount)
  
imports: from collections import namedtuple
  import datetime
  from math import sqrt
  from nose_parameterized import parameterized
  from pandas.tslib import normalize_date
  import numpy
  import pandas
  import pytz
  from catalyst.assets import Equity, Future
  from catalyst.data.data_portal import DataPortal
  from catalyst.finance.asset_restrictions import NoRestrictions
  from catalyst.finance.order import Order
  from catalyst.finance.slippage import EquitySlippageModel, fill_price_worse_than_limit_price, FutureSlippageModel, SlippageModel, VolatilityVolumeShare, VolumeShareSlippage
  from catalyst.protocol import DATASOURCE_TYPE, BarData
  from catalyst.testing import create_minute_bar_data, tmp_bcolz_equity_minute_bar_reader
  from catalyst.testing.fixtures import WithCreateBarData, WithDataPortal, WithSimParams, WithTradingEnvironment, CatalystTestCase
  from catalyst.utils.classproperty import classproperty
label_desc: Use image node_id 9 for calling the VolatilityVolumeShareTestCase obj's underlying member method code with example usage: obj._test_low_transaction_volume() without return types