Merge pull request #1313 from nathanwolfe/master

BUG: Add support for Panel data in accordance with documentation
This commit is contained in:
Joe Jevnik
2016-07-29 20:11:56 -04:00
committed by GitHub
6 changed files with 201 additions and 62 deletions
+85 -1
View File
@@ -33,7 +33,10 @@ import numpy as np
import pandas as pd
import pytz
from zipline import TradingAlgorithm
from zipline import (
run_algorithm,
TradingAlgorithm,
)
from zipline.api import FixedSlippage
from zipline.assets import Equity, Future
from zipline.assets.synthetic import (
@@ -161,6 +164,7 @@ from zipline.test_algorithms import (
no_handle_data,
)
from zipline.utils.api_support import ZiplineAPI, set_algo_instance
from zipline.utils.calendars import get_calendar
from zipline.utils.context_tricks import CallbackManager
from zipline.utils.control_flow import nullctx
import zipline.utils.events
@@ -4102,3 +4106,83 @@ class AlgoInputValidationTestCase(ZiplineTestCase):
script=script,
**{method: lambda *args, **kwargs: None}
)
class TestPanelData(ZiplineTestCase):
@parameterized.expand([
('daily',
pd.Timestamp('2015-12-23', tz='UTC'),
pd.Timestamp('2016-01-05', tz='UTC'),),
('minute',
pd.Timestamp('2015-12-23', tz='UTC'),
pd.Timestamp('2015-12-24', tz='UTC'),),
])
def test_panel_data(self, data_frequency, start_dt, end_dt):
trading_calendar = get_calendar('NYSE')
if data_frequency == 'daily':
history_freq = '1d'
create_df_for_asset = create_daily_df_for_asset
dt_transform = trading_calendar.minute_to_session_label
elif data_frequency == 'minute':
history_freq = '1m'
create_df_for_asset = create_minute_df_for_asset
def dt_transform(dt):
return dt
sids = range(1, 3)
dfs = {}
for sid in sids:
dfs[sid] = create_df_for_asset(trading_calendar,
start_dt, end_dt, interval=sid)
dfs[sid]['prev_close'] = dfs[sid]['close'].shift(1)
panel = pd.Panel(dfs)
price_record = pd.Panel(items=sids,
major_axis=panel.major_axis,
minor_axis=['current', 'previous'])
def initialize(algo):
algo.first_bar = True
algo.equities = []
for sid in sids:
algo.equities.append(algo.sid(sid))
def handle_data(algo, data):
price_record.loc[:, dt_transform(algo.get_datetime()),
'current'] = (
data.current(algo.equities, 'price')
)
if algo.first_bar:
algo.first_bar = False
else:
price_record.loc[:, dt_transform(algo.get_datetime()),
'previous'] = (
data.history(algo.equities, 'price',
2, history_freq).iloc[0]
)
def check_panels():
np.testing.assert_array_equal(
price_record.values.astype('float64'),
panel.loc[:, :, ['close',
'prev_close']].values.astype('float64')
)
trading_algo = TradingAlgorithm(initialize=initialize,
handle_data=handle_data)
trading_algo.run(data=panel)
check_panels()
price_record.loc[:] = np.nan
run_algorithm(
start=start_dt,
end=end_dt,
capital_base=1,
initialize=initialize,
handle_data=handle_data,
data_frequency=data_frequency,
data=panel
)
check_panels()
@@ -18,31 +18,29 @@ from itertools import permutations, product
import numpy as np
import pandas as pd
from zipline.data.us_equity_pricing import PanelDailyBarReader
from zipline.data.us_equity_pricing import PanelBarReader
from zipline.testing import ExplodingObject
from zipline.testing.fixtures import (
WithAssetFinder,
WithNYSETradingDays,
ZiplineTestCase,
)
from zipline.utils.calendars import get_calendar
class TestPanelDailyBarReader(WithAssetFinder,
WithNYSETradingDays,
ZiplineTestCase):
START_DATE = pd.Timestamp('2006-01-03', tz='utc')
END_DATE = pd.Timestamp('2006-02-01', tz='utc')
class WithPanelBarReader(WithAssetFinder):
@classmethod
def init_class_fixtures(cls):
super(TestPanelDailyBarReader, cls).init_class_fixtures()
super(WithPanelBarReader, cls).init_class_fixtures()
finder = cls.asset_finder
days = cls.trading_days
trading_calendar = get_calendar('NYSE')
items = finder.retrieve_all(finder.sids)
major_axis = days
major_axis = (
trading_calendar.sessions_in_range if cls.FREQUENCY == 'daily'
else trading_calendar.minutes_for_sessions_in_range
)(cls.START_DATE, cls.END_DATE)
minor_axis = ['open', 'high', 'low', 'close', 'volume']
shape = tuple(map(len, [items, major_axis, minor_axis]))
@@ -55,7 +53,7 @@ class TestPanelDailyBarReader(WithAssetFinder,
minor_axis=minor_axis,
)
cls.reader = PanelDailyBarReader(days, cls.panel)
cls.reader = PanelBarReader(trading_calendar, cls.panel, cls.FREQUENCY)
def test_spot_price(self):
panel = self.panel
@@ -83,7 +81,7 @@ class TestPanelDailyBarReader(WithAssetFinder,
for axis_order in permutations((0, 1, 2)):
transposed = panel.transpose(*axis_order)
with self.assertRaises(ValueError) as e:
PanelDailyBarReader(unused, transposed)
PanelBarReader(unused, transposed, 'daily')
expected = (
"Duplicate entries in Panel.{name}: ['a', 'b'].".format(
@@ -95,6 +93,28 @@ class TestPanelDailyBarReader(WithAssetFinder,
def test_sessions(self):
sessions = self.reader.sessions
self.assertEqual(21, len(sessions))
self.assertEqual(self.NUM_SESSIONS, len(sessions))
self.assertEqual(self.START_DATE, sessions[0])
self.assertEqual(self.END_DATE, sessions[-1])
class TestPanelDailyBarReader(WithPanelBarReader,
ZiplineTestCase):
FREQUENCY = 'daily'
START_DATE = pd.Timestamp('2006-01-03', tz='utc')
END_DATE = pd.Timestamp('2006-02-01', tz='utc')
NUM_SESSIONS = 21
class TestPanelMinuteBarReader(WithPanelBarReader,
ZiplineTestCase):
FREQUENCY = 'minute'
START_DATE = pd.Timestamp('2015-12-23', tz='utc')
END_DATE = pd.Timestamp('2015-12-24', tz='utc')
NUM_SESSIONS = 2