def _write_data_dicts(self,
equities=None,
futures=None,
exchanges=None,
root_symbols=None):
AssetDBWriterFromDictionary(equities, futures, exchanges, root_symbols)\
.write_all(self.engine)
def __init__(self,
load=None,
bm_symbol='^GSPC',
exchange_tz="US/Eastern",
max_date=None,
env_trading_calendar=tradingcalendar,
asset_db_path=':memory:'):
"""
@load is function that returns benchmark_returns and treasury_curves
The treasury_curves are expected to be a DataFrame with an index of
dates and columns of the curve names, e.g. '10year', '1month', etc.
"""
self.trading_day = env_trading_calendar.trading_day.copy()
# `tc_td` is short for "trading calendar trading days"
tc_td = env_trading_calendar.trading_days
if max_date:
self.trading_days = tc_td[tc_td <= max_date].copy()
else:
self.trading_days = tc_td.copy()
self.first_trading_day = self.trading_days[0]
self.last_trading_day = self.trading_days[-1]
self.early_closes = env_trading_calendar.get_early_closes(
self.first_trading_day, self.last_trading_day)
self.open_and_closes = env_trading_calendar.open_and_closes.loc[
self.trading_days]
self.prev_environment = self
self.bm_symbol = bm_symbol
if not load:
load = load_market_data
self.benchmark_returns, self.treasury_curves = \
load(self.trading_day, self.trading_days, self.bm_symbol)
if max_date:
tr_c = self.treasury_curves
# Mask the treasury curves down to the current date.
# In the case of live trading, the last date in the treasury
# curves would be the day before the date considered to be
# 'today'.
self.treasury_curves = tr_c[tr_c.index <= max_date]
self.exchange_tz = exchange_tz
if isinstance(asset_db_path, string_types):
asset_db_path = 'sqlite:///%s' % asset_db_path
self.engine = engine = create_engine(asset_db_path)
AssetDBWriterFromDictionary().init_db(engine)
else:
self.engine = engine = asset_db_path
if engine is not None:
self.asset_finder = AssetFinder(engine)
else:
self.asset_finder = None
def __init__(
self,
load=None,
bm_symbol='000001',
exchange_tz="Asia/Shanghai",
min_date=None,
max_date=None,
env_trading_calendar=tradingcalendar_china,
asset_db_path=':memory:'
):
"""
@load is function that returns benchmark_returns and treasury_curves
The treasury_curves are expected to be a DataFrame with an index of
dates and columns of the curve names, e.g. '10year', '1month', etc.
# load是返回benchmark_returns和treasury_curves的函数.tourasury_curves应该是一个DataFrame，
# 其中包含曲线名称的日期和列的索引，例如： '10年'，'1个月'等
"""
self.trading_day = env_trading_calendar.trading_day.copy()
# `tc_td` is short for "trading calendar trading days"
tc_td = env_trading_calendar.trading_days
self.trading_days = tc_td[tc_td.slice_indexer(min_date, max_date)]
#print self.trading_day,'trading_days'
self.first_trading_day = self.trading_days[0]
self.last_trading_day = self.trading_days[-1]
#print self.first_trading_day,self.last_trading_day
self.early_closes = env_trading_calendar.get_early_closes(
self.first_trading_day, self.last_trading_day)
self.open_and_closes = env_trading_calendar.open_and_closes.loc[
self.trading_days]
self.bm_symbol = bm_symbol
if not load:
load = load_market_data
# 下面的用于基准每日收益情况，以及国债收益率情况
#print self.trading_day
#print self.trading_days
self.benchmark_returns, self.treasury_curves = \
load(self.trading_day, self.trading_days, self.bm_symbol)
#print self.benchmark_returns
#raw_input()
if max_date:
tr_c = self.treasury_curves
# Mask the treasury curves down to the current date.
# In the case of live trading, the last date in the treasury
# curves would be the day before the date considered to be
# 'today'.
self.treasury_curves = tr_c[tr_c.index <= max_date]
self.exchange_tz = exchange_tz
if isinstance(asset_db_path, string_types):
asset_db_path = 'sqlite:///%s' % asset_db_path
self.engine = engine = create_engine(asset_db_path)
AssetDBWriterFromDictionary().init_db(engine)
else:
self.engine = engine = asset_db_path
if engine is not None:
self.asset_finder = AssetFinder(engine)
else:
self.asset_finder = None
