def mavg(self, intervals, frequency='1d'):
if frequency == 'day':
frequency = '1d'
if frequency == 'minute':
frequency = '1m'
# copy form history
env = Environment.get_instance()
dt = env.calendar_dt
if (env.config.base.frequency == '1m' and frequency == '1d') or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING:
# 在分钟回测获取日线数据, 应该推前一天
dt = env.data_proxy.get_previous_trading_date(env.calendar_dt.date())
bars = env.data_proxy.fast_history(self._instrument.order_book_id, intervals, frequency, 'close', dt)
return bars.mean()
def vwap(self, intervals, frequency='1d'):
if frequency == 'day':
frequency = '1d'
if frequency == 'minute':
frequency = '1m'
# copy form history
env = Environment.get_instance()
dt = env.calendar_dt
if (env.config.base.frequency == '1m' and frequency == '1d') or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING:
# 在分钟回测获取日线数据, 应该推前一天
dt = env.data_proxy.get_previous_trading_date(env.calendar_dt.date())
bars = env.data_proxy.fast_history(self._instrument.order_book_id, intervals, frequency, ['close', 'volume'], dt)
sum = bars['volume'].sum()
if sum == 0:
# 全部停牌
return 0
return np.dot(bars['close'], bars['volume']) / sum
def history_bars(order_book_id,
bar_count,
frequency,
fields=None,
skip_suspended=True,
include_now=False,
adjust_type='pre'):
"""
获取指定合约的历史行情，同时支持日以及分钟历史数据。不能在init中调用。 注意，该API会自动跳过停牌数据。
日回测获取分钟历史数据：不支持
日回测获取日历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日day bar
T日handle_bar T日day bar
========================= ===================================================
分钟回测获取日历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日day bar
T日handle_bar T-1日day bar
========================= ===================================================
分钟回测获取分钟历史数据
========================= ===================================================
调用时间 返回数据
========================= ===================================================
T日before_trading T-1日最后一个minute bar
T日handle_bar T日当前minute bar
========================= ===================================================
:param order_book_id: 合约代码
:type order_book_id: `str`
:param int bar_count: 获取的历史数据数量，必填项
:param str frequency: 获取数据什么样的频率进行。'1d'或'1m'分别表示每日和每分钟，必填项
:param str fields: 返回数据字段。必填项。见下方列表。
========================= ===================================================
fields 字段名
========================= ===================================================
datetime 时间戳
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
total_turnover 成交额
datetime int类型时间戳
open_interest 持仓量（期货专用）
basis_spread 期现差（股指期货专用）
settlement 结算价（期货日线专用）
prev_settlement 结算价（期货日线专用）
========================= ===================================================
:param bool skip_suspended: 是否跳过停牌数据
:param bool include_now: 是否包含当前数据
:param str adjust_type: 复权类型，默认为前复权 pre；可选 pre, none, post
:return: `ndarray`, 方便直接与talib等计算库对接，效率较history返回的DataFrame更高。
:example:
获取最近5天的日线收盘价序列（策略当前日期为20160706）:
.. code-block:: python3
:linenos:
[In]
logger.info(history_bars('000002.XSHE', 5, '1d', 'close'))
[Out]
[ 8.69 8.7 8.71 8.81 8.81]
"""
order_book_id = assure_order_book_id(order_book_id)
env = Environment.get_instance()
dt = env.calendar_dt
if frequency[-1] == 'm' and env.config.base.frequency == '1d':
raise RQInvalidArgument('can not get minute history in day back test')
if adjust_type not in {'pre', 'post', 'none'}:
raise RuntimeError('invalid adjust_type')
if frequency == '1d':
sys_frequency = Environment.get_instance().config.base.frequency
if ((sys_frequency in ['1m', 'tick'] and not include_now)
or ExecutionContext.phase() == EXECUTION_PHASE.BEFORE_TRADING):
dt = env.data_proxy.get_previous_trading_date(
env.trading_dt.date())
# 当 EXECUTION_PHASE.BEFORE_TRADING 的时候，强制 include_now 为 False
include_now = False
if sys_frequency == "1d":
# 日回测不支持 include_now
include_now = False
return env.data_proxy.history_bars(order_book_id,
bar_count,
frequency,
fields,
dt,
skip_suspended=skip_suspended,
include_now=include_now,
adjust_type=adjust_type,
adjust_orig=env.trading_dt)