def test_truncate_between_data_points(self):
tds = self.market_opens.index
days = tds[tds.slice_indexer(
start=self.test_calendar_start + 1,
end=self.test_calendar_start + 3
)]
minutes = DatetimeIndex([
self.market_opens[days[0]] + timedelta(minutes=60),
self.market_opens[days[1]] + timedelta(minutes=120),
])
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0],
'high': [20.0, 21.0],
'low': [30.0, 31.0],
'close': [40.0, 41.0],
'volume': [50.0, 51.0]
},
index=minutes)
self.writer.write_sid(sid, data)
# Open a new writer to cover `open` method, also truncating only
# applies to an existing directory.
writer = BcolzMinuteBarWriter.open(self.dest)
# Truncate to first day with data.
writer.truncate(days[0])
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(self.writer.last_date_in_output_for_sid(sid), days[0])
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(days[0])
self.assertEqual(self.reader.last_available_dt, last_close)
minute = minutes[0]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def test_unadjusted_minutes_early_close(self):
"""
Test unadjusted minute window, ensuring that early closes are filtered
out.
"""
day_before_thanksgiving = Timestamp('2015-11-25', tz='UTC')
xmas_eve = Timestamp('2015-12-24', tz='UTC')
market_day_after_xmas = Timestamp('2015-12-28', tz='UTC')
minutes = [self.market_closes[day_before_thanksgiving] -
Timedelta('2 min'),
self.market_closes[xmas_eve] - Timedelta('1 min'),
self.market_opens[market_day_after_xmas] +
Timedelta('1 min')]
sids = [1, 2]
data_1 = DataFrame(
data={
'open': [
15.0, 15.1, 15.2],
'high': [17.0, 17.1, 17.2],
'low': [11.0, 11.1, 11.3],
'close': [14.0, 14.1, 14.2],
'volume': [1000, 1001, 1002],
},
index=minutes)
self.writer.write_sid(sids[0], data_1)
data_2 = DataFrame(
data={
'open': [25.0, 25.1, 25.2],
'high': [27.0, 27.1, 27.2],
'low': [21.0, 21.1, 21.2],
'close': [24.0, 24.1, 24.2],
'volume': [2000, 2001, 2002],
},
index=minutes)
self.writer.write_sid(sids[1], data_2)
reader = BcolzMinuteBarReader(self.dest)
columns = ['open', 'high', 'low', 'close', 'volume']
sids = [sids[0], sids[1]]
arrays = list(map(transpose, reader.load_raw_arrays(
columns, minutes[0], minutes[-1], sids,
)))
data = {sids[0]: data_1, sids[1]: data_2}
start_minute_loc = \
self.trading_calendar.all_minutes.get_loc(minutes[0])
minute_locs = [
self.trading_calendar.all_minutes.get_loc(minute)
- start_minute_loc
for minute in minutes
]
for i, col in enumerate(columns):
for j, sid in enumerate(sids):
assert_almost_equal(data[sid].loc[minutes, col],
arrays[i][j][minute_locs])
def init_instance_fixtures(self):
super(BcolzMinuteBarTestCase, self).init_instance_fixtures()
self.dest = self.instance_tmpdir.getpath('minute_bars')
os.makedirs(self.dest)
self.writer = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
)
self.reader = BcolzMinuteBarReader(self.dest)
def test_minute_updates(self):
"""
Test minute updates.
"""
start_minute = self.market_opens[TEST_CALENDAR_START]
minutes = [start_minute,
start_minute + Timedelta('1 min'),
start_minute + Timedelta('2 min')]
sids = [1, 2]
data_1 = DataFrame(
data={
'open': [15.0, nan, 15.1],
'high': [17.0, nan, 17.1],
'low': [11.0, nan, 11.1],
'close': [14.0, nan, 14.1],
'volume': [1000, 0, 1001]
},
index=minutes)
data_2 = DataFrame(
data={
'open': [25.0, nan, 25.1],
'high': [27.0, nan, 27.1],
'low': [21.0, nan, 21.1],
'close': [24.0, nan, 24.1],
'volume': [2000, 0, 2001]
},
index=minutes)
frames = {1: data_1, 2: data_2}
update_path = self.instance_tmpdir.getpath('updates.h5')
update_writer = H5MinuteBarUpdateWriter(update_path)
update_writer.write(frames)
update_reader = H5MinuteBarUpdateReader(update_path)
self.writer.write(update_reader.read(minutes, sids))
# Refresh the reader since truncate update the metadata.
reader = BcolzMinuteBarReader(self.dest)
columns = ['open', 'high', 'low', 'close', 'volume']
sids = [sids[0], sids[1]]
arrays = list(map(transpose, reader.load_raw_arrays(
columns, minutes[0], minutes[-1], sids,
)))
data = {sids[0]: data_1, sids[1]: data_2}
for i, col in enumerate(columns):
for j, sid in enumerate(sids):
assert_almost_equal(data[sid][col], arrays[i][j])
def create_data_portal(asset_finder, tempdir, sim_params, sids,
trading_calendar, adjustment_reader=None):
if sim_params.data_frequency == "daily":
daily_path = write_daily_data(tempdir, sim_params, sids,
trading_calendar)
equity_daily_reader = BcolzDailyBarReader(daily_path)
return DataPortal(
asset_finder, trading_calendar,
first_trading_day=equity_daily_reader.first_trading_day,
equity_daily_reader=equity_daily_reader,
adjustment_reader=adjustment_reader
)
else:
minutes = trading_calendar.minutes_in_range(
sim_params.first_open,
sim_params.last_close
)
minute_path = write_minute_data(trading_calendar, tempdir, minutes,
sids)
equity_minute_reader = BcolzMinuteBarReader(minute_path)
return DataPortal(
asset_finder, trading_calendar,
first_trading_day=equity_minute_reader.first_trading_day,
equity_minute_reader=equity_minute_reader,
adjustment_reader=adjustment_reader
)
def test_append_on_new_day(self):
sid = 1
ohlcv = {
'open': [2.0],
'high': [3.0],
'low': [1.0],
'close': [2.0],
'volume': [10.0]
}
dt = self.market_opens[TEST_CALENDAR_STOP]
data = DataFrame(
data=ohlcv,
index=[dt])
self.writer.write_sid(sid, data)
# Open a new writer to cover `open` method, also a common usage
# of appending new days will be writing to an existing directory.
cday = self.trading_calendar.schedule.index.freq
new_end_session = TEST_CALENDAR_STOP + cday
writer = BcolzMinuteBarWriter.open(self.dest, new_end_session)
next_day_minute = dt + cday
new_data = DataFrame(
data=ohlcv,
index=[next_day_minute])
writer.write_sid(sid, new_data)
# Get a new reader to test updated calendar.
reader = BcolzMinuteBarReader(self.dest)
second_minute = dt + Timedelta(minutes=1)
# The second minute should have been padded with zeros
for col in ('open', 'high', 'low', 'close'):
assert_almost_equal(
nan, reader.get_value(sid, second_minute, col)
)
self.assertEqual(
0, reader.get_value(sid, second_minute, 'volume')
)
# The next day minute should have data.
for col in ('open', 'high', 'low', 'close', 'volume'):
assert_almost_equal(
ohlcv[col], reader.get_value(sid, next_day_minute, col)
)
def test_unadjusted_minutes(self):
"""
Test unadjusted minutes.
"""
start_minute = self.market_opens[TEST_CALENDAR_START]
minutes = [start_minute,
start_minute + Timedelta('1 min'),
start_minute + Timedelta('2 min')]
sids = [1, 2]
data_1 = DataFrame(
data={
'open': [15.0, nan, 15.1],
'high': [17.0, nan, 17.1],
'low': [11.0, nan, 11.1],
'close': [14.0, nan, 14.1],
'volume': [1000, 0, 1001]
},
index=minutes)
self.writer.write_sid(sids[0], data_1)
data_2 = DataFrame(
data={
'open': [25.0, nan, 25.1],
'high': [27.0, nan, 27.1],
'low': [21.0, nan, 21.1],
'close': [24.0, nan, 24.1],
'volume': [2000, 0, 2001]
},
index=minutes)
self.writer.write_sid(sids[1], data_2)
reader = BcolzMinuteBarReader(self.dest)
columns = ['open', 'high', 'low', 'close', 'volume']
sids = [sids[0], sids[1]]
arrays = list(map(transpose, reader.load_raw_arrays(
columns, minutes[0], minutes[-1], sids,
)))
data = {sids[0]: data_1, sids[1]: data_2}
for i, col in enumerate(columns):
for j, sid in enumerate(sids):
assert_almost_equal(data[sid][col], arrays[i][j])
def test_truncate_all_data_points(self):
tds = self.market_opens.index
days = tds[tds.slice_indexer(
start=self.test_calendar_start + 1,
end=self.test_calendar_start + 3
)]
minutes = DatetimeIndex([
self.market_opens[days[0]] + timedelta(minutes=60),
self.market_opens[days[1]] + timedelta(minutes=120),
])
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0],
'high': [20.0, 21.0],
'low': [30.0, 31.0],
'close': [40.0, 41.0],
'volume': [50.0, 51.0]
},
index=minutes)
self.writer.write_sid(sid, data)
# Truncate to first day in the calendar, a day before the first
# day with minute data.
self.writer.truncate(self.test_calendar_start)
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(
self.writer.last_date_in_output_for_sid(sid),
self.test_calendar_start,
)
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(
self.test_calendar_start)
self.assertEqual(self.reader.last_available_dt, last_close)
def test_write_one_ohlcv_with_ratios(self):
minute = self.market_opens[self.test_calendar_start]
sid = 1
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0],
},
index=[minute],
)
# Create a new writer with `ohlc_ratios_per_sid` defined.
writer_with_ratios = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
ohlc_ratios_per_sid={sid: 25},
)
writer_with_ratios.write_sid(sid, data)
reader = BcolzMinuteBarReader(self.dest)
open_price = reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def create_data_portal_from_trade_history(asset_finder, trading_calendar,
tempdir, sim_params, trades_by_sid):
if sim_params.data_frequency == "daily":
path = os.path.join(tempdir.path, "testdaily.bcolz")
writer = BcolzDailyBarWriter(
path, trading_calendar,
sim_params.start_session,
sim_params.end_session
)
writer.write(
trades_by_sid_to_dfs(trades_by_sid, sim_params.sessions),
)
equity_daily_reader = BcolzDailyBarReader(path)
return DataPortal(
asset_finder, trading_calendar,
first_trading_day=equity_daily_reader.first_trading_day,
equity_daily_reader=equity_daily_reader,
)
else:
minutes = trading_calendar.minutes_in_range(
sim_params.first_open,
sim_params.last_close
)
length = len(minutes)
assets = {}
for sidint, trades in iteritems(trades_by_sid):
opens = np.zeros(length)
highs = np.zeros(length)
lows = np.zeros(length)
closes = np.zeros(length)
volumes = np.zeros(length)
for trade in trades:
# put them in the right place
idx = minutes.searchsorted(trade.dt)
opens[idx] = trade.open_price * 1000
highs[idx] = trade.high * 1000
lows[idx] = trade.low * 1000
closes[idx] = trade.close_price * 1000
volumes[idx] = trade.volume
assets[sidint] = pd.DataFrame({
"open": opens,
"high": highs,
"low": lows,
"close": closes,
"volume": volumes,
"dt": minutes
}).set_index("dt")
write_bcolz_minute_data(
trading_calendar,
sim_params.sessions,
tempdir.path,
assets
)
equity_minute_reader = BcolzMinuteBarReader(tempdir.path)
return DataPortal(
asset_finder, trading_calendar,
first_trading_day=equity_minute_reader.first_trading_day,
equity_minute_reader=equity_minute_reader,
)
class BcolzMinuteBarTestCase(WithTradingCalendars,
WithAssetFinder,
WithInstanceTmpDir,
GatewayTestCase):
ASSET_FINDER_EQUITY_SIDS = 1, 2
@classmethod
def init_class_fixtures(cls):
super(BcolzMinuteBarTestCase, cls).init_class_fixtures()
cal = cls.trading_calendar.schedule.loc[
TEST_CALENDAR_START:TEST_CALENDAR_STOP
]
cls.market_opens = cal.market_open
cls.market_closes = cal.market_close
cls.test_calendar_start = cls.market_opens.index[0]
cls.test_calendar_stop = cls.market_opens.index[-1]
def init_instance_fixtures(self):
super(BcolzMinuteBarTestCase, self).init_instance_fixtures()
self.dest = self.instance_tmpdir.getpath('minute_bars')
os.makedirs(self.dest)
self.writer = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
)
self.reader = BcolzMinuteBarReader(self.dest)
def test_version(self):
metadata = self.reader._get_metadata()
self.assertEquals(
metadata.version,
BcolzMinuteBarMetadata.FORMAT_VERSION,
)
def test_no_minute_bars_for_sid(self):
minute = self.market_opens[self.test_calendar_start]
with self.assertRaises(NoDataForSid):
self.reader.get_value(1337, minute, 'close')
def test_write_one_ohlcv(self):
minute = self.market_opens[self.test_calendar_start]
sid = 1
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[minute])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def test_write_one_ohlcv_with_ratios(self):
minute = self.market_opens[self.test_calendar_start]
sid = 1
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0],
},
index=[minute],
)
# Create a new writer with `ohlc_ratios_per_sid` defined.
writer_with_ratios = BcolzMinuteBarWriter(
self.dest,
self.trading_calendar,
TEST_CALENDAR_START,
TEST_CALENDAR_STOP,
US_EQUITIES_MINUTES_PER_DAY,
ohlc_ratios_per_sid={sid: 25},
)
writer_with_ratios.write_sid(sid, data)
reader = BcolzMinuteBarReader(self.dest)
open_price = reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def test_write_two_bars(self):
minute_0 = self.market_opens[self.test_calendar_start]
minute_1 = minute_0 + timedelta(minutes=1)
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0],
'high': [20.0, 21.0],
'low': [30.0, 31.0],
'close': [40.0, 41.0],
'volume': [50.0, 51.0]
},
index=[minute_0, minute_1])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute_0, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute_0, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute_0, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute_0, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute_0, 'volume')
self.assertEquals(50.0, volume_price)
open_price = self.reader.get_value(sid, minute_1, 'open')
self.assertEquals(11.0, open_price)
high_price = self.reader.get_value(sid, minute_1, 'high')
self.assertEquals(21.0, high_price)
low_price = self.reader.get_value(sid, minute_1, 'low')
self.assertEquals(31.0, low_price)
close_price = self.reader.get_value(sid, minute_1, 'close')
self.assertEquals(41.0, close_price)
volume_price = self.reader.get_value(sid, minute_1, 'volume')
self.assertEquals(51.0, volume_price)
def test_write_on_second_day(self):
second_day = self.test_calendar_start + 1
minute = self.market_opens[second_day]
sid = 1
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[minute])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def test_write_empty(self):
minute = self.market_opens[self.test_calendar_start]
sid = 1
data = DataFrame(
data={
'open': [0],
'high': [0],
'low': [0],
'close': [0],
'volume': [0]
},
index=[minute])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
assert_almost_equal(nan, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
assert_almost_equal(nan, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
assert_almost_equal(nan, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
assert_almost_equal(nan, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
assert_almost_equal(0, volume_price)
def test_write_on_multiple_days(self):
tds = self.market_opens.index
days = tds[tds.slice_indexer(
start=self.test_calendar_start + 1,
end=self.test_calendar_start + 3
)]
minutes = DatetimeIndex([
self.market_opens[days[0]] + timedelta(minutes=60),
self.market_opens[days[1]] + timedelta(minutes=120),
])
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0],
'high': [20.0, 21.0],
'low': [30.0, 31.0],
'close': [40.0, 41.0],
'volume': [50.0, 51.0]
},
index=minutes)
self.writer.write_sid(sid, data)
minute = minutes[0]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
minute = minutes[1]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(11.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(21.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(31.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(41.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(51.0, volume_price)
def test_no_overwrite(self):
minute = self.market_opens[TEST_CALENDAR_START]
sid = 1
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[minute])
self.writer.write_sid(sid, data)
with self.assertRaises(BcolzMinuteOverlappingData):
self.writer.write_sid(sid, data)
def test_append_to_same_day(self):
"""
Test writing data with the same date as existing data in our file.
"""
sid = 1
first_minute = self.market_opens[TEST_CALENDAR_START]
data = DataFrame(
data={
'open': [10.0],
'high': [20.0],
'low': [30.0],
'close': [40.0],
'volume': [50.0]
},
index=[first_minute])
self.writer.write_sid(sid, data)
# Write data in the same day as the previous minute
second_minute = first_minute + Timedelta(minutes=1)
new_data = DataFrame(
data={
'open': [5.0],
'high': [10.0],
'low': [3.0],
'close': [7.0],
'volume': [10.0]
},
index=[second_minute])
self.writer.write_sid(sid, new_data)
open_price = self.reader.get_value(sid, second_minute, 'open')
self.assertEquals(5.0, open_price)
high_price = self.reader.get_value(sid, second_minute, 'high')
self.assertEquals(10.0, high_price)
low_price = self.reader.get_value(sid, second_minute, 'low')
self.assertEquals(3.0, low_price)
close_price = self.reader.get_value(sid, second_minute, 'close')
self.assertEquals(7.0, close_price)
volume_price = self.reader.get_value(sid, second_minute, 'volume')
self.assertEquals(10.0, volume_price)
def test_append_on_new_day(self):
sid = 1
ohlcv = {
'open': [2.0],
'high': [3.0],
'low': [1.0],
'close': [2.0],
'volume': [10.0]
}
dt = self.market_opens[TEST_CALENDAR_STOP]
data = DataFrame(
data=ohlcv,
index=[dt])
self.writer.write_sid(sid, data)
# Open a new writer to cover `open` method, also a common usage
# of appending new days will be writing to an existing directory.
cday = self.trading_calendar.schedule.index.freq
new_end_session = TEST_CALENDAR_STOP + cday
writer = BcolzMinuteBarWriter.open(self.dest, new_end_session)
next_day_minute = dt + cday
new_data = DataFrame(
data=ohlcv,
index=[next_day_minute])
writer.write_sid(sid, new_data)
# Get a new reader to test updated calendar.
reader = BcolzMinuteBarReader(self.dest)
second_minute = dt + Timedelta(minutes=1)
# The second minute should have been padded with zeros
for col in ('open', 'high', 'low', 'close'):
assert_almost_equal(
nan, reader.get_value(sid, second_minute, col)
)
self.assertEqual(
0, reader.get_value(sid, second_minute, 'volume')
)
# The next day minute should have data.
for col in ('open', 'high', 'low', 'close', 'volume'):
assert_almost_equal(
ohlcv[col], reader.get_value(sid, next_day_minute, col)
)
def test_write_multiple_sids(self):
"""
Test writing multiple sids.
Tests both that the data is written to the correct sid, as well as
ensuring that the logic for creating the subdirectory path to each sid
does not cause issues from attempts to recreate existing paths.
(Calling out this coverage, because an assertion of that logic does not
show up in the test itself, but is exercised by the act of attempting
to write two consecutive sids, which would be written to the same
containing directory, `00/00/000001.bcolz` and `00/00/000002.bcolz)
Before applying a check to make sure the path writing did not
re-attempt directory creation an OSError like the following would
occur:
```
OSError: [Errno 17] File exists: '/tmp/tmpR7yzzT/minute_bars/00/00'
```
"""
minute = self.market_opens[TEST_CALENDAR_START]
sids = [1, 2]
data = DataFrame(
data={
'open': [15.0],
'high': [17.0],
'low': [11.0],
'close': [15.0],
'volume': [100.0]
},
index=[minute])
self.writer.write_sid(sids[0], data)
data = DataFrame(
data={
'open': [25.0],
'high': [27.0],
'low': [21.0],
'close': [25.0],
'volume': [200.0]
},
index=[minute])
self.writer.write_sid(sids[1], data)
sid = sids[0]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(15.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(17.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(11.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(15.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(100.0, volume_price)
sid = sids[1]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(25.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(27.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(21.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(25.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(200.0, volume_price)
def test_pad_data(self):
"""
Test writing empty data.
"""
sid = 1
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertIs(last_date, NaT)
self.writer.pad(sid, TEST_CALENDAR_START)
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertEqual(last_date, TEST_CALENDAR_START)
freq = self.market_opens.index.freq
day = TEST_CALENDAR_START + freq
minute = self.market_opens[day]
data = DataFrame(
data={
'open': [15.0],
'high': [17.0],
'low': [11.0],
'close': [15.0],
'volume': [100.0]
},
index=[minute])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(15.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(17.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(11.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(15.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(100.0, volume_price)
# Check that if we then pad the rest of this day, we end up with
# 2 days worth of minutes.
self.writer.pad(sid, day)
self.assertEqual(
len(self.writer._ensure_ctable(sid)),
self.writer._minutes_per_day * 2,
)
def test_nans(self):
"""
Test writing empty data.
"""
sid = 1
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertIs(last_date, NaT)
self.writer.pad(sid, TEST_CALENDAR_START)
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertEqual(last_date, TEST_CALENDAR_START)
freq = self.market_opens.index.freq
minute = self.market_opens[TEST_CALENDAR_START + freq]
minutes = date_range(minute, periods=9, freq='min')
data = DataFrame(
data={
'open': full(9, nan),
'high': full(9, nan),
'low': full(9, nan),
'close': full(9, nan),
'volume': full(9, 0.0),
},
index=[minutes])
self.writer.write_sid(sid, data)
fields = ['open', 'high', 'low', 'close', 'volume']
ohlcv_window = list(map(transpose, self.reader.load_raw_arrays(
fields, minutes[0], minutes[-1], [sid],
)))
for i, field in enumerate(fields):
if field != 'volume':
assert_array_equal(full(9, nan), ohlcv_window[i][0])
else:
assert_array_equal(zeros(9), ohlcv_window[i][0])
def test_differing_nans(self):
"""
Also test nans of differing values/construction.
"""
sid = 1
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertIs(last_date, NaT)
self.writer.pad(sid, TEST_CALENDAR_START)
last_date = self.writer.last_date_in_output_for_sid(sid)
self.assertEqual(last_date, TEST_CALENDAR_START)
freq = self.market_opens.index.freq
minute = self.market_opens[TEST_CALENDAR_START + freq]
minutes = date_range(minute, periods=9, freq='min')
data = DataFrame(
data={
'open': ((0b11111111111 << 52) + arange(1, 10, dtype=int64)).
view(float64),
'high': ((0b11111111111 << 52) + arange(11, 20, dtype=int64)).
view(float64),
'low': ((0b11111111111 << 52) + arange(21, 30, dtype=int64)).
view(float64),
'close': ((0b11111111111 << 52) + arange(31, 40, dtype=int64)).
view(float64),
'volume': full(9, 0.0),
},
index=[minutes])
self.writer.write_sid(sid, data)
fields = ['open', 'high', 'low', 'close', 'volume']
ohlcv_window = list(map(transpose, self.reader.load_raw_arrays(
fields, minutes[0], minutes[-1], [sid],
)))
for i, field in enumerate(fields):
if field != 'volume':
assert_array_equal(full(9, nan), ohlcv_window[i][0])
else:
assert_array_equal(zeros(9), ohlcv_window[i][0])
def test_write_cols(self):
minute_0 = self.market_opens[self.test_calendar_start]
minute_1 = minute_0 + timedelta(minutes=1)
sid = 1
cols = {
'open': array([10.0, 11.0]),
'high': array([20.0, 21.0]),
'low': array([30.0, 31.0]),
'close': array([40.0, 41.0]),
'volume': array([50.0, 51.0])
}
dts = array([minute_0, minute_1], dtype='datetime64[s]')
self.writer.write_cols(sid, dts, cols)
open_price = self.reader.get_value(sid, minute_0, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute_0, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute_0, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute_0, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute_0, 'volume')
self.assertEquals(50.0, volume_price)
open_price = self.reader.get_value(sid, minute_1, 'open')
self.assertEquals(11.0, open_price)
high_price = self.reader.get_value(sid, minute_1, 'high')
self.assertEquals(21.0, high_price)
low_price = self.reader.get_value(sid, minute_1, 'low')
self.assertEquals(31.0, low_price)
close_price = self.reader.get_value(sid, minute_1, 'close')
self.assertEquals(41.0, close_price)
volume_price = self.reader.get_value(sid, minute_1, 'volume')
self.assertEquals(51.0, volume_price)
def test_write_cols_mismatch_length(self):
dts = date_range(self.market_opens[self.test_calendar_start],
periods=2, freq='min').asi8.astype('datetime64[s]')
sid = 1
cols = {
'open': array([10.0, 11.0, 12.0]),
'high': array([20.0, 21.0]),
'low': array([30.0, 31.0, 33.0, 34.0]),
'close': array([40.0, 41.0]),
'volume': array([50.0, 51.0, 52.0])
}
with self.assertRaises(BcolzMinuteWriterColumnMismatch):
self.writer.write_cols(sid, dts, cols)
def test_unadjusted_minutes(self):
"""
Test unadjusted minutes.
"""
start_minute = self.market_opens[TEST_CALENDAR_START]
minutes = [start_minute,
start_minute + Timedelta('1 min'),
start_minute + Timedelta('2 min')]
sids = [1, 2]
data_1 = DataFrame(
data={
'open': [15.0, nan, 15.1],
'high': [17.0, nan, 17.1],
'low': [11.0, nan, 11.1],
'close': [14.0, nan, 14.1],
'volume': [1000, 0, 1001]
},
index=minutes)
self.writer.write_sid(sids[0], data_1)
data_2 = DataFrame(
data={
'open': [25.0, nan, 25.1],
'high': [27.0, nan, 27.1],
'low': [21.0, nan, 21.1],
'close': [24.0, nan, 24.1],
'volume': [2000, 0, 2001]
},
index=minutes)
self.writer.write_sid(sids[1], data_2)
reader = BcolzMinuteBarReader(self.dest)
columns = ['open', 'high', 'low', 'close', 'volume']
sids = [sids[0], sids[1]]
arrays = list(map(transpose, reader.load_raw_arrays(
columns, minutes[0], minutes[-1], sids,
)))
data = {sids[0]: data_1, sids[1]: data_2}
for i, col in enumerate(columns):
for j, sid in enumerate(sids):
assert_almost_equal(data[sid][col], arrays[i][j])
def test_unadjusted_minutes_early_close(self):
"""
Test unadjusted minute window, ensuring that early closes are filtered
out.
"""
day_before_thanksgiving = Timestamp('2015-11-25', tz='UTC')
xmas_eve = Timestamp('2015-12-24', tz='UTC')
market_day_after_xmas = Timestamp('2015-12-28', tz='UTC')
minutes = [self.market_closes[day_before_thanksgiving] -
Timedelta('2 min'),
self.market_closes[xmas_eve] - Timedelta('1 min'),
self.market_opens[market_day_after_xmas] +
Timedelta('1 min')]
sids = [1, 2]
data_1 = DataFrame(
data={
'open': [
15.0, 15.1, 15.2],
'high': [17.0, 17.1, 17.2],
'low': [11.0, 11.1, 11.3],
'close': [14.0, 14.1, 14.2],
'volume': [1000, 1001, 1002],
},
index=minutes)
self.writer.write_sid(sids[0], data_1)
data_2 = DataFrame(
data={
'open': [25.0, 25.1, 25.2],
'high': [27.0, 27.1, 27.2],
'low': [21.0, 21.1, 21.2],
'close': [24.0, 24.1, 24.2],
'volume': [2000, 2001, 2002],
},
index=minutes)
self.writer.write_sid(sids[1], data_2)
reader = BcolzMinuteBarReader(self.dest)
columns = ['open', 'high', 'low', 'close', 'volume']
sids = [sids[0], sids[1]]
arrays = list(map(transpose, reader.load_raw_arrays(
columns, minutes[0], minutes[-1], sids,
)))
data = {sids[0]: data_1, sids[1]: data_2}
start_minute_loc = \
self.trading_calendar.all_minutes.get_loc(minutes[0])
minute_locs = [
self.trading_calendar.all_minutes.get_loc(minute)
- start_minute_loc
for minute in minutes
]
for i, col in enumerate(columns):
for j, sid in enumerate(sids):
assert_almost_equal(data[sid].loc[minutes, col],
arrays[i][j][minute_locs])
def test_adjust_non_trading_minutes(self):
start_day = Timestamp('2015-06-01', tz='UTC')
end_day = Timestamp('2015-06-02', tz='UTC')
sid = 1
cols = {
'open': arange(1, 781),
'high': arange(1, 781),
'low': arange(1, 781),
'close': arange(1, 781),
'volume': arange(1, 781)
}
dts = array(self.trading_calendar.minutes_for_sessions_in_range(
self.trading_calendar.minute_to_session_label(start_day),
self.trading_calendar.minute_to_session_label(end_day)
))
self.writer.write_cols(sid, dts, cols)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-06-01 20:00:00', tz='UTC'),
'open'),
390)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-06-02 20:00:00', tz='UTC'),
'open'),
780)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(
sid,
Timestamp('2015-06-02', tz='UTC'),
'open'
)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(
sid,
Timestamp('2015-06-02 20:01:00', tz='UTC'),
'open'
)
def test_adjust_non_trading_minutes_half_days(self):
# half day
start_day = Timestamp('2015-11-27', tz='UTC')
end_day = Timestamp('2015-11-30', tz='UTC')
sid = 1
cols = {
'open': arange(1, 601),
'high': arange(1, 601),
'low': arange(1, 601),
'close': arange(1, 601),
'volume': arange(1, 601)
}
dts = array(
self.trading_calendar.minutes_for_sessions_in_range(
self.trading_calendar.minute_to_session_label(start_day),
self.trading_calendar.minute_to_session_label(end_day)
)
)
self.writer.write_cols(sid, dts, cols)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-11-27 18:00:00', tz='UTC'),
'open'),
210)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-11-30 21:00:00', tz='UTC'),
'open'),
600)
self.assertEqual(
self.reader.get_value(
sid,
Timestamp('2015-11-27 18:01:00', tz='UTC'),
'open'),
210)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(
sid,
Timestamp('2015-11-30', tz='UTC'),
'open'
)
with self.assertRaises(NoDataOnDate):
self.reader.get_value(
sid,
Timestamp('2015-11-30 21:01:00', tz='UTC'),
'open'
)
def test_set_sid_attrs(self):
"""Confirm that we can set the attributes of a sid's file correctly.
"""
sid = 1
start_day = Timestamp('2015-11-27', tz='UTC')
end_day = Timestamp('2015-06-02', tz='UTC')
attrs = {
'start_day': start_day.value / int(1e9),
'end_day': end_day.value / int(1e9),
'factor': 100,
}
# Write the attributes
self.writer.set_sid_attrs(sid, **attrs)
# Read the attributes
for k, v in attrs.items():
self.assertEqual(self.reader.get_sid_attr(sid, k), v)
def test_truncate_between_data_points(self):
tds = self.market_opens.index
days = tds[tds.slice_indexer(
start=self.test_calendar_start + 1,
end=self.test_calendar_start + 3
)]
minutes = DatetimeIndex([
self.market_opens[days[0]] + timedelta(minutes=60),
self.market_opens[days[1]] + timedelta(minutes=120),
])
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0],
'high': [20.0, 21.0],
'low': [30.0, 31.0],
'close': [40.0, 41.0],
'volume': [50.0, 51.0]
},
index=minutes)
self.writer.write_sid(sid, data)
# Open a new writer to cover `open` method, also truncating only
# applies to an existing directory.
writer = BcolzMinuteBarWriter.open(self.dest)
# Truncate to first day with data.
writer.truncate(days[0])
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(self.writer.last_date_in_output_for_sid(sid), days[0])
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(days[0])
self.assertEqual(self.reader.last_available_dt, last_close)
minute = minutes[0]
open_price = self.reader.get_value(sid, minute, 'open')
self.assertEquals(10.0, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
self.assertEquals(20.0, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
self.assertEquals(30.0, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
self.assertEquals(40.0, close_price)
volume_price = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(50.0, volume_price)
def test_truncate_all_data_points(self):
tds = self.market_opens.index
days = tds[tds.slice_indexer(
start=self.test_calendar_start + 1,
end=self.test_calendar_start + 3
)]
minutes = DatetimeIndex([
self.market_opens[days[0]] + timedelta(minutes=60),
self.market_opens[days[1]] + timedelta(minutes=120),
])
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0],
'high': [20.0, 21.0],
'low': [30.0, 31.0],
'close': [40.0, 41.0],
'volume': [50.0, 51.0]
},
index=minutes)
self.writer.write_sid(sid, data)
# Truncate to first day in the calendar, a day before the first
# day with minute data.
self.writer.truncate(self.test_calendar_start)
# Refresh the reader since truncate update the metadata.
self.reader = BcolzMinuteBarReader(self.dest)
self.assertEqual(
self.writer.last_date_in_output_for_sid(sid),
self.test_calendar_start,
)
cal = self.trading_calendar
_, last_close = cal.open_and_close_for_session(
self.test_calendar_start)
self.assertEqual(self.reader.last_available_dt, last_close)
def test_early_market_close(self):
# Date to test is 2015-11-30 9:31
# Early close is 2015-11-27 18:00
friday_after_tday = Timestamp('2015-11-27', tz='UTC')
friday_after_tday_close = self.market_closes[friday_after_tday]
before_early_close = friday_after_tday_close - timedelta(minutes=8)
after_early_close = friday_after_tday_close + timedelta(minutes=8)
monday_after_tday = Timestamp('2015-11-30', tz='UTC')
minute = self.market_opens[monday_after_tday]
# Test condition where there is data written after the market
# close (ideally, this should not occur in datasets, but guards
# against consumers of the minute bar writer, which do not filter
# out after close minutes.
minutes = [
before_early_close,
after_early_close,
minute,
]
sid = 1
data = DataFrame(
data={
'open': [10.0, 11.0, nan],
'high': [20.0, 21.0, nan],
'low': [30.0, 31.0, nan],
'close': [40.0, 41.0, nan],
'volume': [50, 51, 0]
},
index=[minutes])
self.writer.write_sid(sid, data)
open_price = self.reader.get_value(sid, minute, 'open')
assert_almost_equal(nan, open_price)
high_price = self.reader.get_value(sid, minute, 'high')
assert_almost_equal(nan, high_price)
low_price = self.reader.get_value(sid, minute, 'low')
assert_almost_equal(nan, low_price)
close_price = self.reader.get_value(sid, minute, 'close')
assert_almost_equal(nan, close_price)
volume = self.reader.get_value(sid, minute, 'volume')
self.assertEquals(0, volume)
asset = self.asset_finder.retrieve_asset(sid)
last_traded_dt = self.reader.get_last_traded_dt(asset, minute)
self.assertEquals(last_traded_dt, before_early_close,
"The last traded dt should be before the early "
"close, even when data is written between the early "
"close and the next open.")
def test_minute_updates(self):
"""
Test minute updates.
"""
start_minute = self.market_opens[TEST_CALENDAR_START]
minutes = [start_minute,
start_minute + Timedelta('1 min'),
start_minute + Timedelta('2 min')]
sids = [1, 2]
data_1 = DataFrame(
data={
'open': [15.0, nan, 15.1],
'high': [17.0, nan, 17.1],
'low': [11.0, nan, 11.1],
'close': [14.0, nan, 14.1],
'volume': [1000, 0, 1001]
},
index=minutes)
data_2 = DataFrame(
data={
'open': [25.0, nan, 25.1],
'high': [27.0, nan, 27.1],
'low': [21.0, nan, 21.1],
'close': [24.0, nan, 24.1],
'volume': [2000, 0, 2001]
},
index=minutes)
frames = {1: data_1, 2: data_2}
update_path = self.instance_tmpdir.getpath('updates.h5')
update_writer = H5MinuteBarUpdateWriter(update_path)
update_writer.write(frames)
update_reader = H5MinuteBarUpdateReader(update_path)
self.writer.write(update_reader.read(minutes, sids))
# Refresh the reader since truncate update the metadata.
reader = BcolzMinuteBarReader(self.dest)
columns = ['open', 'high', 'low', 'close', 'volume']
sids = [sids[0], sids[1]]
arrays = list(map(transpose, reader.load_raw_arrays(
columns, minutes[0], minutes[-1], sids,
)))
data = {sids[0]: data_1, sids[1]: data_2}
for i, col in enumerate(columns):
for j, sid in enumerate(sids):
assert_almost_equal(data[sid][col], arrays[i][j])
def transaction_sim(self, **params):
"""This is a utility method that asserts expected
results for conversion of orders to transactions given a
trade history
"""
trade_count = params['trade_count']
trade_interval = params['trade_interval']
order_count = params['order_count']
order_amount = params['order_amount']
order_interval = params['order_interval']
expected_txn_count = params['expected_txn_count']
expected_txn_volume = params['expected_txn_volume']
# optional parameters
# ---------------------
# if present, alternate between long and short sales
alternate = params.get('alternate')
# if present, expect transaction amounts to match orders exactly.
complete_fill = params.get('complete_fill')
asset1 = self.asset_finder.retrieve_asset(1)
metadata = make_simple_equity_info([asset1.sid], self.start, self.end)
with TempDirectory() as tempdir, \
tmp_trading_env(equities=metadata,
load=self.make_load_function()) as env:
if trade_interval < timedelta(days=1):
sim_params = factory.create_simulation_parameters(
start=self.start, end=self.end, data_frequency="minute")
minutes = self.trading_calendar.minutes_window(
sim_params.first_open,
int((trade_interval.total_seconds() / 60) * trade_count) +
100)
price_data = np.array([10.1] * len(minutes))
assets = {
asset1.sid:
pd.DataFrame({
"open": price_data,
"high": price_data,
"low": price_data,
"close": price_data,
"volume": np.array([100] * len(minutes)),
"dt": minutes
}).set_index("dt")
}
write_bcolz_minute_data(
self.trading_calendar,
self.trading_calendar.sessions_in_range(
self.trading_calendar.minute_to_session_label(
minutes[0]),
self.trading_calendar.minute_to_session_label(
minutes[-1])),
tempdir.path,
iteritems(assets),
)
equity_minute_reader = BcolzMinuteBarReader(tempdir.path)
data_portal = DataPortal(
env.asset_finder,
self.trading_calendar,
first_trading_day=equity_minute_reader.first_trading_day,
equity_minute_reader=equity_minute_reader,
)
else:
sim_params = factory.create_simulation_parameters(
data_frequency="daily")
days = sim_params.sessions
assets = {
1:
pd.DataFrame(
{
"open": [10.1] * len(days),
"high": [10.1] * len(days),
"low": [10.1] * len(days),
"close": [10.1] * len(days),
"volume": [100] * len(days),
"day": [day.value for day in days]
},
index=days)
}
path = os.path.join(tempdir.path, "testdata.bcolz")
BcolzDailyBarWriter(path, self.trading_calendar, days[0],
days[-1]).write(assets.items())
equity_daily_reader = BcolzDailyBarReader(path)
data_portal = DataPortal(
env.asset_finder,
self.trading_calendar,
first_trading_day=equity_daily_reader.first_trading_day,
equity_daily_reader=equity_daily_reader,
)
if "default_slippage" not in params or \
not params["default_slippage"]:
slippage_func = FixedSlippage()
else:
slippage_func = None
blotter = Blotter(sim_params.data_frequency, slippage_func)
start_date = sim_params.first_open
if alternate:
alternator = -1
else:
alternator = 1
tracker = PerformanceTracker(sim_params, self.trading_calendar,
self.env)
# replicate what tradesim does by going through every minute or day
# of the simulation and processing open orders each time
if sim_params.data_frequency == "minute":
ticks = minutes
else:
ticks = days
transactions = []
order_list = []
order_date = start_date
for tick in ticks:
blotter.current_dt = tick
if tick >= order_date and len(order_list) < order_count:
# place an order
direction = alternator**len(order_list)
order_id = blotter.order(asset1, order_amount * direction,
MarketOrder())
order_list.append(blotter.orders[order_id])
order_date = order_date + order_interval
# move after market orders to just after market next
# market open.
if order_date.hour >= 21:
if order_date.minute >= 00:
order_date = order_date + timedelta(days=1)
order_date = order_date.replace(hour=14, minute=30)
else:
bar_data = BarData(
data_portal=data_portal,
simulation_dt_func=lambda: tick,
data_frequency=sim_params.data_frequency,
trading_calendar=self.trading_calendar,
restrictions=NoRestrictions(),
)
txns, _, closed_orders = blotter.get_transactions(bar_data)
for txn in txns:
tracker.process_transaction(txn)
transactions.append(txn)
blotter.prune_orders(closed_orders)
for i in range(order_count):
order = order_list[i]
self.assertEqual(order.asset, asset1)
self.assertEqual(order.amount, order_amount * alternator**i)
if complete_fill:
self.assertEqual(len(transactions), len(order_list))
total_volume = 0
for i in range(len(transactions)):
txn = transactions[i]
total_volume += txn.amount
if complete_fill:
order = order_list[i]
self.assertEqual(order.amount, txn.amount)
self.assertEqual(total_volume, expected_txn_volume)
self.assertEqual(len(transactions), expected_txn_count)
cumulative_pos = tracker.position_tracker.positions[asset1]
if total_volume == 0:
self.assertIsNone(cumulative_pos)
else:
self.assertEqual(total_volume, cumulative_pos.amount)
# the open orders should not contain the asset.
oo = blotter.open_orders
self.assertNotIn(asset1, oo,
"Entry is removed when no open orders")