def get_benchmark_values(self, dates):
# 不管几点，要对应整点的的日级数据
# start = str_to_timestamp(str((str_to_datetime(dates[0]) - datetime.timedelta(days=self.refresh_rate)).date()))
start = str2timestamp(
str((str2datetime(dates[0]) - datetime.timedelta(days=1)).date()))
end = str2timestamp(str((str2datetime(dates[-1])).date()))
bm_values = self.benchmark.loc[(self.benchmark["timestamp"] >= start)
& (self.benchmark["timestamp"] <= end)]
# bm_values = bm_values.loc[bm_values.index[::self.refresh_rate]]['close'].tolist()
bm_values = bm_values['close'].tolist()
return bm_values
def __init__(self,
start_date=None,
end_date=None,
frequency=None,
refresh_rate=None,
trigger_time=None):
"""
:param start_date: 初始日期
:param end_date: 结束日期
"""
self._str_date = start_date + ' ' + trigger_time[
0] if trigger_time else start_date
self._current_date = str2datetime(self._str_date) # 当前日期 datetime
self._previous_date = None
self._current_timestamp = None # 当前日期 时间戳
self._end_timestamp = str2timestamp(end_date) # 结束日期 时间戳
self._bars = 0
self._bars_m = 0 # 开始bars数量
self._bars_start = 0
self._day_bar = 0
self._run_start = time.time() # 记录run运行时间
self._datestart = time.time()
self._run_end = None
self._frequency = frequency
self._refresh_rate = refresh_rate
async def _handle_data(self):
# print("******************************************************************")
clock = self.context.clock
current_date = clock.current_date
logger.current_date = current_date
current_timestamp = clock.current_timestamp
# print(current_date)
prebars=clock.pre_bar
pre_start = str(str2datetime(self.start) - datetime.timedelta(days=prebars))
try:
if not self.cache_data:
self.cache_data = self.context.prepare_data(self.universe, self.all_assets, self.benchmark,
self.frequency, pre_start, self.end, self.timezone)
except Exception:
output({"display_type": "error",
"error_msg": traceback.format_exc()})
return 1
# 记录初始持仓
start = self.start + ' ' + self.trigger_time[0] if self.trigger_time else self.start # 只支持一个trigger_time
if current_timestamp == str2timestamp(start):
for name, account in self.portfolio.accounts.items():
for asset, position in account.current_position.items():
position.context = self.context
init_portfolio_position = dict()
for asset in self.context.asset_varieties:
init_pp_detail = PortfolioPosition(self.context, asset, self.portfolio.accounts).detail()
init_portfolio_position[asset] = init_pp_detail
self.context.init_portfolio_position = init_portfolio_position
self.context.init_position_total = sum([asset['total_amount'] for asset in init_portfolio_position.values()])
self.context.init_total_account_position = {}
for name in self.context.accounts_name:
name_position = "{}_position".format(name)
total_amount = 0
for asset,value in self.context.init_portfolio_position.items():
if name in value['consist_of'].keys():
total_amount += value['consist_of'][name]['amount']
self.context.init_total_account_position[name_position] = total_amount
# logger.info('【记录初始持仓时间】：{} s'.format(str(time.time() - start2)[:5]))
try:
if str(current_date) in self.strategy_dates:
self.handle_data(self.context)
except Exception:
output({"display_type": "error",
"error_msg": traceback.format_exc()})
return 1
self.portfolio.record_history()
def get_benchmark_values(self, dates):
# 不管几点，要对应整点的的日级数据
# start = str_to_timestamp(str((str_to_datetime(dates[0]) - datetime.timedelta(days=self.refresh_rate)).date()))
if self.context.frequency in ['d', '1d', 'day', '1day']:
start = str((str2datetime(dates[0]) -
datetime.timedelta(days=self.refresh_rate)))
end = str((str2datetime(dates[-1])))
bm_values = self.benchmark.loc[
(self.benchmark["timestamp"] >= start)
& (self.benchmark["timestamp"] <= end)]
bm_values = bm_values.loc[
bm_values.index[::self.refresh_rate]]['close'].tolist()
else:
start = str((
str2datetime(dates[0]) -
datetime.timedelta(days=1))) #benchmarkvalue只取对应基准的日价值，所以每日值都取
end = str((str2datetime(dates[-1])))
bm_values = self.benchmark.loc[
(self.benchmark["timestamp"] >= start)
& (self.benchmark["timestamp"] <= end)]
bm_values = bm_values['close'].tolist()
return bm_values
def get_dates_values_positions_orders(self):
"""
:return: dates、values、positions、orders
"""
values = list()
dates = list()
portfolio_position = dict()
orders = dict()
benchmarks = self.benchmark
values.append(self.context.init_position_total)
for date, pf in self.rebalance_history.items():
values.append(
sum([
asset['total_amount']
for asset in pf['portfolio_position']['detail'].values()
]))
dates.append(date)
portfolio_position[date] = pf['portfolio_position']
orders[date] = pf['orders']
date1 = []
value1 = []
portfolio_position1 = dict()
orders1 = dict()
freq1 = self.context.frequency
if freq1 in ['d', '1d', 'day', '1day']:
for i, v in enumerate(dates):
if v in benchmarks['timestamp'].values:
date1.append(dates[i])
value1.append(values[i])
portfolio_position1[dates[i]] = portfolio_position[
dates[i]]
orders1[dates[i]] = orders[dates[i]]
else:
for i, v in enumerate(dates):
if v in benchmarks['timestamp'].values:
countbar = 0
maxnum = random.uniform(5, 10)
date1.append(dates[i])
value1.append(values[i])
portfolio_position1[dates[i]] = portfolio_position[
dates[i]]
if orders[dates[i]]:
currentdate = str2datetime(dates[i]).replace(hour=0,
minute=0,
second=0,
microsecond=0)
if bool(orders1):
if (str(currentdate)) not in orders1.keys():
orders1[str(currentdate)] = []
tempdate = list(orders1.keys())[-1]
orderdate = str2datetime(tempdate).replace(
hour=0, minute=0, second=0, microsecond=0)
if currentdate == orderdate:
countbar += 1
if countbar <= maxnum:
orders1[str(currentdate)].append(
orders[dates[i]][0])
else:
orders1[str(currentdate)].append(
orders[dates[i]][0])
else:
currentdate = str2datetime(dates[i]).replace(
hour=0, minute=0, second=0, microsecond=0)
orders1[str(currentdate)] = []
orders1[str(currentdate)].append(orders[dates[i]][0])
dates = date1
values = value1
portfolio_position = portfolio_position1
orders = orders1
return dates, values, portfolio_position, orders
