def test_semi_active_day(self):
# on self.bcolz_daily_bar_days[0], only asset1 has data
bar_data = BarData(
self.data_portal,
lambda: self.bcolz_daily_bar_days[0],
"daily",
)
self.check_internal_consistency(bar_data)
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
# because there is real data
self.assertFalse(bar_data.is_stale(self.ASSET1))
# because there has never been a trade bar yet
self.assertFalse(bar_data.is_stale(self.ASSET2))
self.assertEqual(3, bar_data.current(self.ASSET1, "open"))
self.assertEqual(4, bar_data.current(self.ASSET1, "high"))
self.assertEqual(1, bar_data.current(self.ASSET1, "low"))
self.assertEqual(2, bar_data.current(self.ASSET1, "close"))
self.assertEqual(200, bar_data.current(self.ASSET1, "volume"))
self.assertEqual(2, bar_data.current(self.ASSET1, "price"))
self.assertEqual(self.bcolz_daily_bar_days[0],
bar_data.current(self.ASSET1, "last_traded"))
for field in OHLCP:
self.assertTrue(np.isnan(bar_data.current(self.ASSET2, field)),
field)
self.assertEqual(0, bar_data.current(self.ASSET2, "volume"))
self.assertTrue(bar_data.current(self.ASSET2, "last_traded") is pd.NaT)
def test_last_active_day(self):
bar_data = BarData(
self.data_portal,
lambda: self.get_last_minute_of_session(
self.equity_daily_bar_days[-1]
),
"daily",
self.trading_calendar
)
self.check_internal_consistency(bar_data)
for asset in self.ASSETS:
if asset in (1, 2):
self.assertFalse(bar_data.can_trade(asset))
else:
self.assertTrue(bar_data.can_trade(asset))
self.assertFalse(bar_data.is_stale(asset))
if asset in (1, 2):
assert_almost_equal(nan, bar_data.current(asset, "open"))
assert_almost_equal(nan, bar_data.current(asset, "high"))
assert_almost_equal(nan, bar_data.current(asset, "low"))
assert_almost_equal(nan, bar_data.current(asset, "close"))
assert_almost_equal(0, bar_data.current(asset, "volume"))
assert_almost_equal(nan, bar_data.current(asset, "price"))
else:
self.assertEqual(6, bar_data.current(asset, "open"))
self.assertEqual(7, bar_data.current(asset, "high"))
self.assertEqual(4, bar_data.current(asset, "low"))
self.assertEqual(5, bar_data.current(asset, "close"))
self.assertEqual(500, bar_data.current(asset, "volume"))
self.assertEqual(5, bar_data.current(asset, "price"))
def test_can_trade_at_midnight(self):
# make sure that if we use `can_trade` at midnight, we don't pretend
# we're in the previous day's last minute
the_day_after = self.env.next_trading_day(
self.bcolz_minute_bar_days[-1],
)
bar_data = BarData(self.data_portal, lambda: the_day_after, "minute")
for asset in [self.ASSET1, self.HILARIOUSLY_ILLIQUID_ASSET]:
self.assertFalse(bar_data.can_trade(asset))
with handle_non_market_minutes(bar_data):
self.assertFalse(bar_data.can_trade(asset))
# but make sure it works when the assets are alive
bar_data2 = BarData(
self.data_portal,
lambda: self.bcolz_minute_bar_days[1],
"minute",
)
for asset in [self.ASSET1, self.HILARIOUSLY_ILLIQUID_ASSET]:
self.assertTrue(bar_data2.can_trade(asset))
with handle_non_market_minutes(bar_data2):
self.assertTrue(bar_data2.can_trade(asset))
def test_semi_active_day(self):
# on self.days[0], only asset1 has data
bar_data = BarData(self.data_portal, lambda: self.days[0], "daily")
self.check_internal_consistency(bar_data)
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
# because there is real data
self.assertFalse(bar_data.is_stale(self.ASSET1))
# because there has never been a trade bar yet
self.assertFalse(bar_data.is_stale(self.ASSET2))
self.assertEqual(3, bar_data.current(self.ASSET1, "open"))
self.assertEqual(4, bar_data.current(self.ASSET1, "high"))
self.assertEqual(1, bar_data.current(self.ASSET1, "low"))
self.assertEqual(2, bar_data.current(self.ASSET1, "close"))
self.assertEqual(200, bar_data.current(self.ASSET1, "volume"))
self.assertEqual(2, bar_data.current(self.ASSET1, "price"))
self.assertEqual(self.days[0],
bar_data.current(self.ASSET1, "last_traded"))
for field in OHLCP:
self.assertTrue(np.isnan(bar_data.current(self.ASSET2, field)),
field)
self.assertEqual(0, bar_data.current(self.ASSET2, "volume"))
self.assertTrue(
bar_data.current(self.ASSET2, "last_traded") is pd.NaT
)
def test_can_trade_equity_same_cal_no_last_price(self):
# self.HILARIOUSLY_ILLIQUID_ASSET's first trade is at
# 2016-01-05 15:20:00+00:00. Make sure that can_trade returns false
# for all minutes in that session before the first trade, and true
# for all minutes afterwards.
cal = get_calendar(self.ASSET1.exchange)
minutes_in_session = cal.minutes_for_session(self.ASSET1.start_date)
for minute in minutes_in_session[0:49]:
bar_data = BarData(
self.data_portal, lambda: minute, "minute", cal
)
self.assertFalse(bar_data.can_trade(
self.HILARIOUSLY_ILLIQUID_ASSET)
)
for minute in minutes_in_session[50:]:
bar_data = BarData(
self.data_portal, lambda: minute, "minute", cal
)
self.assertTrue(bar_data.can_trade(
self.HILARIOUSLY_ILLIQUID_ASSET)
)
def test_can_trade_at_midnight(self):
# make sure that if we use `can_trade` at midnight, we don't pretend
# we're in the previous day's last minute
the_day_after = self.env.next_trading_day(
self.bcolz_minute_bar_days[-1], )
bar_data = BarData(self.data_portal, lambda: the_day_after, "minute")
for asset in [self.ASSET1, self.HILARIOUSLY_ILLIQUID_ASSET]:
self.assertFalse(bar_data.can_trade(asset))
with handle_non_market_minutes(bar_data):
self.assertFalse(bar_data.can_trade(asset))
# but make sure it works when the assets are alive
bar_data2 = BarData(
self.data_portal,
lambda: self.bcolz_minute_bar_days[1],
"minute",
)
for asset in [self.ASSET1, self.HILARIOUSLY_ILLIQUID_ASSET]:
self.assertTrue(bar_data2.can_trade(asset))
with handle_non_market_minutes(bar_data2):
self.assertTrue(bar_data2.can_trade(asset))
def test_after_assets_dead(self):
# both assets end on self.day[-1], so let's try the next day
minute = self.get_last_minute_of_session(
self.trading_calendar.next_session_label(
self.equity_daily_bar_days[-1]))
bar_data = BarData(self.data_portal, lambda: minute, "daily")
self.check_internal_consistency(bar_data)
for asset in self.ASSETS:
self.assertFalse(bar_data.can_trade(asset))
self.assertFalse(bar_data.is_stale(asset))
for field in OHLCP:
self.assertTrue(np.isnan(bar_data.current(asset, field)))
self.assertEqual(0, bar_data.current(asset, "volume"))
last_traded_dt = bar_data.current(asset, "last_traded")
if asset == self.ASSET1:
self.assertEqual(self.equity_daily_bar_days[-2],
last_traded_dt)
else:
self.assertEqual(self.equity_daily_bar_days[1], last_traded_dt)
def test_after_assets_dead(self):
# both assets end on self.day[-1], so let's try the next day
next_day = self.trading_schedule.next_execution_day(
self.equity_daily_bar_days[-1]
)
bar_data = BarData(self.data_portal, lambda: next_day, "daily")
self.check_internal_consistency(bar_data)
for asset in self.ASSETS:
self.assertFalse(bar_data.can_trade(asset))
self.assertFalse(bar_data.is_stale(asset))
for field in OHLCP:
self.assertTrue(np.isnan(bar_data.current(asset, field)))
self.assertEqual(0, bar_data.current(asset, "volume"))
last_traded_dt = bar_data.current(asset, "last_traded")
if asset == self.ASSET1:
self.assertEqual(self.equity_daily_bar_days[-2],
last_traded_dt)
else:
self.assertEqual(self.equity_daily_bar_days[1], last_traded_dt)
def test_minute_after_assets_stopped(self):
minutes = self.env.market_minutes_for_day(
self.env.next_trading_day(self.days[-1]))
last_trading_minute = \
self.env.market_minutes_for_day(self.days[-1])[-1]
# this entire day is after both assets have stopped trading
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.assertFalse(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET2))
self.check_internal_consistency(bar_data)
for field in ALL_FIELDS:
for asset in self.ASSETS:
asset_value = bar_data.current(asset, field)
if field in OHLCP:
self.assertTrue(np.isnan(asset_value))
elif field == "volume":
self.assertEqual(0, asset_value)
elif field == "last_traded":
self.assertEqual(last_trading_minute, asset_value)
def test_day_before_assets_trading(self):
# use the day before self.bcolz_daily_bar_days[0]
minute = self.get_last_minute_of_session(
self.trading_calendar.previous_session_label(
self.equity_daily_bar_days[0]
)
)
bar_data = BarData(self.data_portal, lambda: minute, "daily",
self.trading_calendar)
self.check_internal_consistency(bar_data)
self.assertFalse(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET2))
for field in ALL_FIELDS:
for asset in self.ASSETS:
asset_value = bar_data.current(asset, field)
if field in OHLCP:
self.assertTrue(np.isnan(asset_value))
elif field == "volume":
self.assertEqual(0, asset_value)
elif field == "last_traded":
self.assertTrue(asset_value is pd.NaT)
def test_minute_after_assets_stopped(self):
minutes = self.env.market_minutes_for_day(
self.env.next_trading_day(self.days[-1])
)
last_trading_minute = \
self.env.market_minutes_for_day(self.days[-1])[-1]
# this entire day is after both assets have stopped trading
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.assertFalse(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET2))
self.check_internal_consistency(bar_data)
for field in ALL_FIELDS:
for asset in self.ASSETS:
asset_value = bar_data.current(asset, field)
if field in OHLCP:
self.assertTrue(np.isnan(asset_value))
elif field == "volume":
self.assertEqual(0, asset_value)
elif field == "last_traded":
self.assertEqual(last_trading_minute, asset_value)
def test_minute_before_assets_trading(self):
# grab minutes that include the day before the asset start
minutes = self.env.market_minutes_for_day(
self.env.previous_trading_day(self.days[0]))
# this entire day is before either asset has started trading
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.check_internal_consistency(bar_data)
self.assertFalse(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET2))
for field in ALL_FIELDS:
for asset in self.ASSETS:
asset_value = bar_data.current(asset, field)
if field in OHLCP:
self.assertTrue(np.isnan(asset_value))
elif field == "volume":
self.assertEqual(0, asset_value)
elif field == "last_traded":
self.assertTrue(asset_value is pd.NaT)
def validateSectorUniverse(candidate_sector_universe: Universe,
zipline_data: BarData):
"""Function to validate a candidate sector universe. Ensures that
Zipline can look up all tickers.
Arguments:
candidate_sector_universe {Universe} -- Candidate sector universe.
zipline_data {BarData} -- Instance zipline data bundle.
Raises:
SymbolNotFound -- Raised when a symbol is not found.
"""
for ticker in candidate_sector_universe.getUniqueTickers():
try:
symbol(ticker)
if not zipline_data.can_trade(symbol(ticker)):
raise NoDataForSid
except (SymbolNotFound, NoDataForSid):
# Updating invalid ticker in the universe
candidate_sector_universe.removeInvalidTicker(
invalid_ticker=ticker)
logging.info(
'Ticker {0} in universe not in Zipline; removing'.format(
ticker))
# Return 'clean' sector universe
return candidate_sector_universe
def test_day_before_assets_trading(self):
# use the day before self.equity_daily_bar_days[0]
day = self.trading_schedule.previous_execution_day(
self.equity_daily_bar_days[0]
)
bar_data = BarData(self.data_portal, lambda: day, "daily")
self.check_internal_consistency(bar_data)
self.assertFalse(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET2))
for field in ALL_FIELDS:
for asset in self.ASSETS:
asset_value = bar_data.current(asset, field)
if field in OHLCP:
self.assertTrue(np.isnan(asset_value))
elif field == "volume":
self.assertEqual(0, asset_value)
elif field == "last_traded":
self.assertTrue(asset_value is pd.NaT)
def test_fully_active_day(self):
bar_data = BarData(
self.data_portal,
lambda: self.get_last_minute_of_session(
self.equity_daily_bar_days[1]
),
"daily",
self.trading_calendar
)
self.check_internal_consistency(bar_data)
# on self.equity_daily_bar_days[1], both assets have data
for asset in self.ASSETS:
self.assertTrue(bar_data.can_trade(asset))
self.assertFalse(bar_data.is_stale(asset))
self.assertEqual(4, bar_data.current(asset, "open"))
self.assertEqual(5, bar_data.current(asset, "high"))
self.assertEqual(2, bar_data.current(asset, "low"))
self.assertEqual(3, bar_data.current(asset, "close"))
self.assertEqual(300, bar_data.current(asset, "volume"))
self.assertEqual(3, bar_data.current(asset, "price"))
self.assertEqual(
self.equity_daily_bar_days[1],
bar_data.current(asset, "last_traded")
)
def test_minute_before_assets_trading(self):
# grab minutes that include the day before the asset start
minutes = self.env.market_minutes_for_day(
self.env.previous_trading_day(self.days[0])
)
# this entire day is before either asset has started trading
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.check_internal_consistency(bar_data)
self.assertFalse(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET2))
for field in ALL_FIELDS:
for asset in self.ASSETS:
asset_value = bar_data.current(asset, field)
if field in OHLCP:
self.assertTrue(np.isnan(asset_value))
elif field == "volume":
self.assertEqual(0, asset_value)
elif field == "last_traded":
self.assertTrue(asset_value is pd.NaT)
def test_minute_of_last_day(self):
minutes = self.env.market_minutes_for_day(self.days[-1])
# this is the last day the assets exist
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertTrue(bar_data.can_trade(self.ASSET2))
def test_minute_of_last_day(self):
minutes = self.env.market_minutes_for_day(self.days[-1])
# this is the last day the assets exist
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertTrue(bar_data.can_trade(self.ASSET2))
def test_can_trade_equity_same_cal_outside_lifetime(self):
cal = get_calendar(self.ASSET1.exchange)
# verify that can_trade returns False for the session before the
# asset's first session
session_before_asset1_start = cal.previous_session_label(
self.ASSET1.start_date
)
minutes_for_session = cal.minutes_for_session(
session_before_asset1_start
)
# for good measure, check the minute before the session too
minutes_to_check = chain(
[minutes_for_session[0] - pd.Timedelta(minutes=1)],
minutes_for_session
)
for minute in minutes_to_check:
bar_data = BarData(
self.data_portal, lambda: minute, "minute", cal
)
self.assertFalse(bar_data.can_trade(self.ASSET1))
# after asset lifetime
session_after_asset1_end = cal.next_session_label(
self.ASSET1.end_date
)
bts_after_asset1_end = session_after_asset1_end.replace(
hour=8, minute=45
).tz_convert(None).tz_localize("US/Eastern")
minutes_to_check = chain(
cal.minutes_for_session(session_after_asset1_end),
[bts_after_asset1_end]
)
for minute in minutes_to_check:
bar_data = BarData(
self.data_portal, lambda: minute, "minute", cal
)
self.assertFalse(bar_data.can_trade(self.ASSET1))
def test_minute_of_last_day(self):
minutes = self.trading_calendar.minutes_for_session(
self.equity_daily_bar_days[-1], )
# this is the last day the assets exist
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertTrue(bar_data.can_trade(self.ASSET2))
def test_minute_of_last_day(self):
minutes = self.trading_schedule.execution_minutes_for_day(
self.bcolz_daily_bar_days[-1], )
# this is the last day the assets exist
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertTrue(bar_data.can_trade(self.ASSET2))
def test_minute_of_last_day(self):
minutes = self.trading_schedule.execution_minutes_for_day(
self.equity_daily_bar_days[-1],
)
# this is the last day the assets exist
for idx, minute in enumerate(minutes):
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertTrue(bar_data.can_trade(self.ASSET2))
def test_last_active_day(self):
bar_data = BarData(self.data_portal, lambda: self.days[-1], "daily")
self.check_internal_consistency(bar_data)
for asset in self.ASSETS:
self.assertTrue(bar_data.can_trade(asset))
self.assertFalse(bar_data.is_stale(asset))
self.assertEqual(6, bar_data.current(asset, "open"))
self.assertEqual(7, bar_data.current(asset, "high"))
self.assertEqual(4, bar_data.current(asset, "low"))
self.assertEqual(5, bar_data.current(asset, "close"))
self.assertEqual(500, bar_data.current(asset, "volume"))
self.assertEqual(5, bar_data.current(asset, "price"))
def test_last_active_day(self):
bar_data = BarData(self.data_portal, lambda: self.days[-1], "daily")
self.check_internal_consistency(bar_data)
for asset in self.ASSETS:
self.assertTrue(bar_data.can_trade(asset))
self.assertFalse(bar_data.is_stale(asset))
self.assertEqual(6, bar_data.current(asset, "open"))
self.assertEqual(7, bar_data.current(asset, "high"))
self.assertEqual(4, bar_data.current(asset, "low"))
self.assertEqual(5, bar_data.current(asset, "close"))
self.assertEqual(500, bar_data.current(asset, "volume"))
self.assertEqual(5, bar_data.current(asset, "price"))
def test_can_trade_multiple_exchange_closed(self):
nyse_asset = self.asset_finder.retrieve_asset(1)
ice_asset = self.asset_finder.retrieve_asset(6)
# minutes we're going to check (to verify that that the same bardata
# can check multiple exchange calendars, all times Eastern):
# 2016-01-05:
# 20:00 (minute before ICE opens)
# 20:01 (first minute of ICE session)
# 20:02 (second minute of ICE session)
# 00:00 (Cinderella's ride becomes a pumpkin)
# 2016-01-06:
# 9:30 (minute before NYSE opens)
# 9:31 (first minute of NYSE session)
# 9:32 (second minute of NYSE session)
# 15:59 (second-to-last minute of NYSE session)
# 16:00 (last minute of NYSE session)
# 16:01 (minute after NYSE closed)
# 17:59 (second-to-last minute of ICE session)
# 18:00 (last minute of ICE session)
# 18:01 (minute after ICE closed)
# each row is dt, whether-nyse-is-open, whether-ice-is-open
minutes_to_check = [
(pd.Timestamp("2016-01-05 20:00", tz="US/Eastern"), False, False),
(pd.Timestamp("2016-01-05 20:01", tz="US/Eastern"), False, True),
(pd.Timestamp("2016-01-05 20:02", tz="US/Eastern"), False, True),
(pd.Timestamp("2016-01-06 00:00", tz="US/Eastern"), False, True),
(pd.Timestamp("2016-01-06 9:30", tz="US/Eastern"), False, True),
(pd.Timestamp("2016-01-06 9:31", tz="US/Eastern"), True, True),
(pd.Timestamp("2016-01-06 9:32", tz="US/Eastern"), True, True),
(pd.Timestamp("2016-01-06 15:59", tz="US/Eastern"), True, True),
(pd.Timestamp("2016-01-06 16:00", tz="US/Eastern"), True, True),
(pd.Timestamp("2016-01-06 16:01", tz="US/Eastern"), False, True),
(pd.Timestamp("2016-01-06 17:59", tz="US/Eastern"), False, True),
(pd.Timestamp("2016-01-06 18:00", tz="US/Eastern"), False, True),
(pd.Timestamp("2016-01-06 18:01", tz="US/Eastern"), False, False),
]
for info in minutes_to_check:
# use the CME calendar, which covers 24 hours
bar_data = BarData(self.data_portal, lambda: info[0], "minute",
trading_calendar=get_calendar("CME"))
series = bar_data.can_trade([nyse_asset, ice_asset])
self.assertEqual(info[1], series.loc[nyse_asset])
self.assertEqual(info[2], series.loc[ice_asset])
def test_can_trade_equity_same_cal_exchange_closed(self):
cal = get_calendar(self.ASSET1.exchange)
# verify that can_trade returns true for minutes that are
# outside the asset's calendar (assuming the asset is alive and
# there is a last price), because the asset is alive on the
# next market minute.
minutes = cal.minutes_for_sessions_in_range(
self.ASSET1.start_date,
self.ASSET1.end_date
)
for minute in minutes:
bar_data = BarData(
self.data_portal, lambda: minute, "minute", cal
)
self.assertTrue(bar_data.can_trade(self.ASSET1))
def test_after_assets_dead(self):
session = self.END_DATE
bar_data = BarData(self.data_portal, lambda: session, "daily",
self.trading_calendar)
self.check_internal_consistency(bar_data)
for asset in self.ASSETS:
self.assertFalse(bar_data.can_trade(asset))
self.assertFalse(bar_data.is_stale(asset))
for field in OHLCP:
self.assertTrue(np.isnan(bar_data.current(asset, field)))
self.assertEqual(0, bar_data.current(asset, "volume"))
last_traded_dt = bar_data.current(asset, "last_traded")
if asset in (self.ASSET1, self.ASSET2):
self.assertEqual(self.equity_daily_bar_days[3],
last_traded_dt)
def test_after_assets_dead(self):
# both assets end on self.day[-1], so let's try the next day
next_day = self.env.next_trading_day(self.days[-1])
bar_data = BarData(self.data_portal, lambda: next_day, "daily")
self.check_internal_consistency(bar_data)
for asset in self.ASSETS:
self.assertFalse(bar_data.can_trade(asset))
self.assertFalse(bar_data.is_stale(asset))
for field in OHLCP:
self.assertTrue(np.isnan(bar_data.current(asset, field)))
self.assertEqual(0, bar_data.current(asset, "volume"))
last_traded_dt = bar_data.current(asset, "last_traded")
if asset == self.ASSET1:
self.assertEqual(self.days[-2], last_traded_dt)
else:
self.assertEqual(self.days[1], last_traded_dt)
def test_day_before_assets_trading(self):
# use the day before self.days[0]
day = self.env.previous_trading_day(self.days[0])
bar_data = BarData(self.data_portal, lambda: day, "daily")
self.check_internal_consistency(bar_data)
self.assertFalse(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET2))
for field in ALL_FIELDS:
for asset in self.ASSETS:
asset_value = bar_data.current(asset, field)
if field in OHLCP:
self.assertTrue(np.isnan(asset_value))
elif field == "volume":
self.assertEqual(0, asset_value)
elif field == "last_traded":
self.assertTrue(asset_value is pd.NaT)
def test_regular_minute(self):
minutes = self.env.market_minutes_for_day(self.days[0])
for idx, minute in enumerate(minutes):
# day2 has prices
# (every minute for asset1, every 10 minutes for asset2)
# asset1:
# opens: 2-391
# high: 3-392
# low: 0-389
# close: 1-390
# volume: 100-3900 (by 100)
# asset2 is the same thing, but with only every 10th minute
# populated.
# this test covers the "IPO morning" case, because asset2 only
# has data starting on the 10th minute.
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.check_internal_consistency(bar_data)
asset2_has_data = (((idx + 1) % 10) == 0)
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET1))
if idx < 9:
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET2))
else:
self.assertTrue(bar_data.can_trade(self.ASSET2))
if asset2_has_data:
self.assertFalse(bar_data.is_stale(self.ASSET2))
else:
self.assertTrue(bar_data.is_stale(self.ASSET2))
for field in ALL_FIELDS:
asset1_value = bar_data.current(self.ASSET1, field)
asset2_value = bar_data.current(self.ASSET2, field)
# now check the actual values
if idx == 0 and field == "low":
# first low value is 0, which is interpreted as NaN
self.assertTrue(np.isnan(asset1_value))
else:
if field in OHLC:
self.assertEqual(idx + 1 + field_info[field],
asset1_value)
if asset2_has_data:
self.assertEqual(idx + 1 + field_info[field],
asset2_value)
else:
self.assertTrue(np.isnan(asset2_value))
elif field == "volume":
self.assertEqual((idx + 1) * 100, asset1_value)
if asset2_has_data:
self.assertEqual((idx + 1) * 100, asset2_value)
else:
self.assertEqual(0, asset2_value)
elif field == "price":
self.assertEqual(idx + 1, asset1_value)
if asset2_has_data:
self.assertEqual(idx + 1, asset2_value)
elif idx < 9:
# no price to forward fill from
self.assertTrue(np.isnan(asset2_value))
else:
# forward-filled price
self.assertEqual((idx // 10) * 10, asset2_value)
elif field == "last_traded":
self.assertEqual(minute, asset1_value)
if idx < 9:
self.assertTrue(asset2_value is pd.NaT)
elif asset2_has_data:
self.assertEqual(minute, asset2_value)
else:
last_traded_minute = minutes[(idx // 10) * 10]
self.assertEqual(last_traded_minute - 1,
asset2_value)
def test_regular_minute(self):
minutes = self.env.market_minutes_for_day(self.days[0])
for idx, minute in enumerate(minutes):
# day2 has prices
# (every minute for asset1, every 10 minutes for asset2)
# asset1:
# opens: 2-391
# high: 3-392
# low: 0-389
# close: 1-390
# volume: 100-3900 (by 100)
# asset2 is the same thing, but with only every 10th minute
# populated.
# this test covers the "IPO morning" case, because asset2 only
# has data starting on the 10th minute.
bar_data = BarData(self.data_portal, lambda: minute, "minute")
self.check_internal_consistency(bar_data)
asset2_has_data = (((idx + 1) % 10) == 0)
self.assertTrue(bar_data.can_trade(self.ASSET1))
self.assertFalse(bar_data.is_stale(self.ASSET1))
if idx < 9:
self.assertFalse(bar_data.can_trade(self.ASSET2))
self.assertFalse(bar_data.is_stale(self.ASSET2))
else:
self.assertTrue(bar_data.can_trade(self.ASSET2))
if asset2_has_data:
self.assertFalse(bar_data.is_stale(self.ASSET2))
else:
self.assertTrue(bar_data.is_stale(self.ASSET2))
for field in ALL_FIELDS:
asset1_value = bar_data.current(self.ASSET1, field)
asset2_value = bar_data.current(self.ASSET2, field)
# now check the actual values
if idx == 0 and field == "low":
# first low value is 0, which is interpreted as NaN
self.assertTrue(np.isnan(asset1_value))
else:
if field in OHLC:
self.assertEqual(
idx + 1 + field_info[field],
asset1_value
)
if asset2_has_data:
self.assertEqual(
idx + 1 + field_info[field],
asset2_value
)
else:
self.assertTrue(np.isnan(asset2_value))
elif field == "volume":
self.assertEqual((idx + 1) * 100, asset1_value)
if asset2_has_data:
self.assertEqual((idx + 1) * 100, asset2_value)
else:
self.assertEqual(0, asset2_value)
elif field == "price":
self.assertEqual(idx + 1, asset1_value)
if asset2_has_data:
self.assertEqual(idx + 1, asset2_value)
elif idx < 9:
# no price to forward fill from
self.assertTrue(np.isnan(asset2_value))
else:
# forward-filled price
self.assertEqual((idx // 10) * 10, asset2_value)
elif field == "last_traded":
self.assertEqual(minute, asset1_value)
if idx < 9:
self.assertTrue(asset2_value is pd.NaT)
elif asset2_has_data:
self.assertEqual(minute, asset2_value)
else:
last_traded_minute = minutes[(idx // 10) * 10]
self.assertEqual(last_traded_minute - 1,
asset2_value)
