本文整理汇总了Python中zipline.finance.trading.TradingEnvironment类的典型用法代码示例。如果您正苦于以下问题：Python TradingEnvironment类的具体用法？Python TradingEnvironment怎么用？Python TradingEnvironment使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了TradingEnvironment类的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: TestChangeOfSids
class TestChangeOfSids(TestCase):
def setUp(self):
self.sids = range(90)
self.env = TradingEnvironment()
self.env.write_data(equities_identifiers=self.sids)
self.sim_params = factory.create_simulation_parameters(
start=datetime(1990, 1, 1, tzinfo=pytz.utc),
end=datetime(1990, 1, 8, tzinfo=pytz.utc),
env=self.env,
)
def test_all_sids_passed(self):
algo = BatchTransformAlgorithmSetSid(
sim_params=self.sim_params,
env=self.env,
)
source = DifferentSidSource()
algo.run(source)
for i, (df, date) in enumerate(zip(algo.history, source.trading_days)):
self.assertEqual(df.index[-1], date, "Newest event doesn't \
match.")
for sid in self.sids[:i]:
self.assertIn(sid, df.columns)
self.assertEqual(df.iloc[-1].iloc[-1], i)示例2: test_compute_lifetimes
def test_compute_lifetimes(self):
num_assets = 4
env = TradingEnvironment()
trading_day = env.trading_day
first_start = pd.Timestamp('2015-04-01', tz='UTC')
frame = make_rotating_asset_info(
num_assets=num_assets,
first_start=first_start,
frequency=env.trading_day,
periods_between_starts=3,
asset_lifetime=5
)
env.write_data(equities_df=frame)
finder = env.asset_finder
all_dates = pd.date_range(
start=first_start,
end=frame.end_date.max(),
freq=trading_day,
)
for dates in all_subindices(all_dates):
expected_with_start_raw = full(
shape=(len(dates), num_assets),
fill_value=False,
dtype=bool,
)
expected_no_start_raw = full(
shape=(len(dates), num_assets),
fill_value=False,
dtype=bool,
)
for i, date in enumerate(dates):
it = frame[['start_date', 'end_date']].itertuples()
for j, start, end in it:
# This way of doing the checks is redundant, but very
# clear.
if start <= date <= end:
expected_with_start_raw[i, j] = True
if start < date:
expected_no_start_raw[i, j] = True
expected_with_start = pd.DataFrame(
data=expected_with_start_raw,
index=dates,
columns=frame.index.values,
)
result = finder.lifetimes(dates, include_start_date=True)
assert_frame_equal(result, expected_with_start)
expected_no_start = pd.DataFrame(
data=expected_no_start_raw,
index=dates,
columns=frame.index.values,
)
result = finder.lifetimes(dates, include_start_date=False)
assert_frame_equal(result, expected_no_start)示例3: create_test_df_source
def create_test_df_source(sim_params=None, env=None, bars='daily'):
if bars == 'daily':
freq = pd.datetools.BDay()
elif bars == 'minute':
freq = pd.datetools.Minute()
else:
raise ValueError('%s bars not understood.' % bars)
if sim_params and bars == 'daily':
index = sim_params.trading_days
else:
if env is None:
env = TradingEnvironment()
start = pd.datetime(1990, 1, 3, 0, 0, 0, 0, pytz.utc)
end = pd.datetime(1990, 1, 8, 0, 0, 0, 0, pytz.utc)
days = env.days_in_range(start, end)
if bars == 'daily':
index = days
if bars == 'minute':
index = pd.DatetimeIndex([], freq=freq)
for day in days:
day_index = env.market_minutes_for_day(day)
index = index.append(day_index)
x = np.arange(1, len(index) + 1)
df = pd.DataFrame(x, index=index, columns=[0])
return DataFrameSource(df), df示例4: setUpClass
def setUpClass(cls):
metadata = {
0: {
'symbol': 'CLG06',
'root_symbol': 'CL',
'start_date': pd.Timestamp('2005-12-01', tz='UTC'),
'notice_date': pd.Timestamp('2005-12-20', tz='UTC'),
'expiration_date': pd.Timestamp('2006-01-20', tz='UTC')},
1: {
'root_symbol': 'CL',
'symbol': 'CLK06',
'start_date': pd.Timestamp('2005-12-01', tz='UTC'),
'notice_date': pd.Timestamp('2006-03-20', tz='UTC'),
'expiration_date': pd.Timestamp('2006-04-20', tz='UTC')},
2: {
'symbol': 'CLQ06',
'root_symbol': 'CL',
'start_date': pd.Timestamp('2005-12-01', tz='UTC'),
'notice_date': pd.Timestamp('2006-06-20', tz='UTC'),
'expiration_date': pd.Timestamp('2006-07-20', tz='UTC')},
3: {
'symbol': 'CLX06',
'root_symbol': 'CL',
'start_date': pd.Timestamp('2006-02-01', tz='UTC'),
'notice_date': pd.Timestamp('2006-09-20', tz='UTC'),
'expiration_date': pd.Timestamp('2006-10-20', tz='UTC')}
}
env = TradingEnvironment(load=noop_load)
env.write_data(futures_data=metadata)
cls.asset_finder = env.asset_finder示例5: create_test_panel_source
def create_test_panel_source(sim_params=None, env=None, source_type=None):
start = sim_params.first_open \
if sim_params else pd.datetime(1990, 1, 3, 0, 0, 0, 0, pytz.utc)
end = sim_params.last_close \
if sim_params else pd.datetime(1990, 1, 8, 0, 0, 0, 0, pytz.utc)
if env is None:
env = TradingEnvironment()
index = env.days_in_range(start, end)
price = np.arange(0, len(index))
volume = np.ones(len(index)) * 1000
arbitrary = np.ones(len(index))
df = pd.DataFrame({'price': price,
'volume': volume,
'arbitrary': arbitrary},
index=index)
if source_type:
source_types = np.full(len(index), source_type)
df['type'] = source_types
panel = pd.Panel.from_dict({0: df})
return DataPanelSource(panel), panel示例6: setUp
def setUp(self):
self.constants = {
# Every day, assume every stock starts at 2, goes down to 1,
# goes up to 4, and finishes at 3.
USEquityPricing.low: 1,
USEquityPricing.open: 2,
USEquityPricing.close: 3,
USEquityPricing.high: 4,
}
self.asset_ids = [1, 2, 3, 4]
self.dates = date_range('2014-01', '2014-03', freq='D', tz='UTC')
self.loader = PrecomputedLoader(
constants=self.constants,
dates=self.dates,
sids=self.asset_ids,
)
self.asset_info = make_simple_equity_info(
self.asset_ids,
start_date=self.dates[0],
end_date=self.dates[-1],
)
environment = TradingEnvironment()
environment.write_data(equities_df=self.asset_info)
self.asset_finder = environment.asset_finder
self.assets = self.asset_finder.retrieve_all(self.asset_ids)示例7: setUpClass
def setUpClass(cls):
metadata = {
0: {
"symbol": "CLG06",
"root_symbol": "CL",
"start_date": pd.Timestamp("2005-12-01", tz="UTC"),
"notice_date": pd.Timestamp("2005-12-20", tz="UTC"),
"expiration_date": pd.Timestamp("2006-01-20", tz="UTC"),
},
1: {
"root_symbol": "CL",
"symbol": "CLK06",
"start_date": pd.Timestamp("2005-12-01", tz="UTC"),
"notice_date": pd.Timestamp("2006-03-20", tz="UTC"),
"expiration_date": pd.Timestamp("2006-04-20", tz="UTC"),
},
2: {
"symbol": "CLQ06",
"root_symbol": "CL",
"start_date": pd.Timestamp("2005-12-01", tz="UTC"),
"notice_date": pd.Timestamp("2006-06-20", tz="UTC"),
"expiration_date": pd.Timestamp("2006-07-20", tz="UTC"),
},
3: {
"symbol": "CLX06",
"root_symbol": "CL",
"start_date": pd.Timestamp("2006-02-01", tz="UTC"),
"notice_date": pd.Timestamp("2006-09-20", tz="UTC"),
"expiration_date": pd.Timestamp("2006-10-20", tz="UTC"),
},
}
env = TradingEnvironment(load=noop_load)
env.write_data(futures_data=metadata)
cls.asset_finder = env.asset_finder示例8: test_yahoo_bars_to_panel_source
def test_yahoo_bars_to_panel_source(self):
env = TradingEnvironment()
finder = AssetFinder(env.engine)
stocks = ['AAPL', 'GE']
env.write_data(equities_identifiers=stocks)
start = pd.datetime(1993, 1, 1, 0, 0, 0, 0, pytz.utc)
end = pd.datetime(2002, 1, 1, 0, 0, 0, 0, pytz.utc)
data = factory.load_bars_from_yahoo(stocks=stocks,
indexes={},
start=start,
end=end)
check_fields = ['sid', 'open', 'high', 'low', 'close',
'volume', 'price']
copy_panel = data.copy()
sids = finder.map_identifier_index_to_sids(
data.items, data.major_axis[0]
)
copy_panel.items = sids
source = DataPanelSource(copy_panel)
for event in source:
for check_field in check_fields:
self.assertIn(check_field, event)
self.assertTrue(isinstance(event['volume'], (integer_types)))
self.assertTrue(event['sid'] in sids)示例9: setUp
def setUp(self):
self.assets = [1, 2, 3]
self.dates = date_range("2014-01", "2014-03", freq="D", tz="UTC")
asset_info = make_simple_asset_info(self.assets, start_date=self.dates[0], end_date=self.dates[-1])
env = TradingEnvironment()
env.write_data(equities_df=asset_info)
self.asset_finder = env.asset_finder示例10: test_sids
def test_sids(self):
# Ensure that the sids property of the AssetFinder is functioning
env = TradingEnvironment()
env.write_data(equities_identifiers=[1, 2, 3])
sids = env.asset_finder.sids
self.assertEqual(3, len(sids))
self.assertTrue(1 in sids)
self.assertTrue(2 in sids)
self.assertTrue(3 in sids)示例11: setUp
def setUp(self):
self.assets = [1, 2, 3]
self.dates = date_range('2014-01-01', '2014-02-01', freq='D', tz='UTC')
asset_info = make_simple_asset_info(
self.assets,
start_date=self.dates[0],
end_date=self.dates[-1],
)
env = TradingEnvironment()
env.write_data(equities_df=asset_info)
self.asset_finder = env.asset_finder示例12: setUpClass
def setUpClass(cls):
cls.test_data_dir = TempDirectory()
cls.db_path = cls.test_data_dir.getpath("adjustments.db")
all_days = TradingEnvironment().trading_days
cls.calendar_days = all_days[all_days.slice_indexer(TEST_CALENDAR_START, TEST_CALENDAR_STOP)]
daily_bar_reader = MockDailyBarSpotReader()
writer = SQLiteAdjustmentWriter(cls.db_path, cls.calendar_days, daily_bar_reader)
writer.write(SPLITS, MERGERS, DIVIDENDS)
cls.assets = TEST_QUERY_ASSETS
cls.asset_info = EQUITY_INFO
cls.bcolz_writer = SyntheticDailyBarWriter(cls.asset_info, cls.calendar_days)
cls.bcolz_path = cls.test_data_dir.getpath("equity_pricing.bcolz")
cls.bcolz_writer.write(cls.bcolz_path, cls.calendar_days, cls.assets)示例13: setUp
def setUp(self):
self.__calendar = date_range('2014', '2015', freq=trading_day)
self.__assets = assets = Int64Index(arange(1, 20))
# Set up env for test
env = TradingEnvironment()
env.write_data(
equities_df=make_simple_asset_info(
assets,
self.__calendar[0],
self.__calendar[-1],
))
self.__finder = env.asset_finder
self.__mask = self.__finder.lifetimes(self.__calendar[-10:])示例14: test_trading_environment
def test_trading_environment(self):
benchmark_returns, treasury_curves = \
factory.load_market_data()
env = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=datetime(2008, 1, 1, tzinfo=pytz.utc),
period_end=datetime(2008, 12, 31, tzinfo=pytz.utc),
capital_base=100000,
)
#holidays taken from: http://www.nyse.com/press/1191407641943.html
new_years = datetime(2008, 1, 1, tzinfo=pytz.utc)
mlk_day = datetime(2008, 1, 21, tzinfo=pytz.utc)
presidents = datetime(2008, 2, 18, tzinfo=pytz.utc)
good_friday = datetime(2008, 3, 21, tzinfo=pytz.utc)
memorial_day = datetime(2008, 5, 26, tzinfo=pytz.utc)
july_4th = datetime(2008, 7, 4, tzinfo=pytz.utc)
labor_day = datetime(2008, 9, 1, tzinfo=pytz.utc)
tgiving = datetime(2008, 11, 27, tzinfo=pytz.utc)
christmas = datetime(2008, 5, 25, tzinfo=pytz.utc)
a_saturday = datetime(2008, 8, 2, tzinfo=pytz.utc)
a_sunday = datetime(2008, 10, 12, tzinfo=pytz.utc)
holidays = [
new_years,
mlk_day,
presidents,
good_friday,
memorial_day,
july_4th,
labor_day,
tgiving,
christmas,
a_saturday,
a_sunday
]
for holiday in holidays:
self.assertTrue(not env.is_trading_day(holiday))
first_trading_day = datetime(2008, 1, 2, tzinfo=pytz.utc)
last_trading_day = datetime(2008, 12, 31, tzinfo=pytz.utc)
workdays = [first_trading_day, last_trading_day]
for workday in workdays:
self.assertTrue(env.is_trading_day(workday))
self.assertTrue(env.last_close.month == 12)
self.assertTrue(env.last_close.day == 31)示例15: test_compute_lifetimes
def test_compute_lifetimes(self):
num_assets = 4
env = TradingEnvironment()
trading_day = env.trading_day
first_start = pd.Timestamp('2015-04-01', tz='UTC')
frame = make_rotating_asset_info(
num_assets=num_assets,
first_start=first_start,
frequency=env.trading_day,
periods_between_starts=3,
asset_lifetime=5
)
env.write_data(equities_df=frame)
finder = env.asset_finder
all_dates = pd.date_range(
start=first_start,
end=frame.end_date.max(),
freq=trading_day,
)
for dates in all_subindices(all_dates):
expected_mask = full(
shape=(len(dates), num_assets),
fill_value=False,
dtype=bool,
)
for i, date in enumerate(dates):
it = frame[['start_date', 'end_date']].itertuples()
for j, start, end in it:
if start <= date <= end:
expected_mask[i, j] = True
# Filter out columns with all-empty columns.
expected_result = pd.DataFrame(
data=expected_mask,
index=dates,
columns=frame.index.values,
)
actual_result = finder.lifetimes(dates)
assert_frame_equal(actual_result, expected_result)