def load_bar(self, vt_symbol: str, days: int, interval: Interval,
callback: Callable[[BarData], None]):
""""""
symbol, exchange = extract_vt_symbol(vt_symbol)
end = datetime.now()
start = end - timedelta(days)
# Query bars from gateway if available
contract = self.main_engine.get_contract(vt_symbol)
if contract and contract.history_data:
req = HistoryRequest(symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end)
bars = self.main_engine.query_history(req, contract.gateway_name)
# Try to query bars from RQData, if not found, load from database.
else:
bars = self.query_bar_from_rq(symbol, exchange, interval, start,
end)
if not bars:
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
for bar in bars:
callback(bar)
def data_step(self, index_info: IndexInfo):
"""
数据准备阶段
:param index_info:
:return:
"""
newest_bar = database_manager.get_newest_bar_data(
index_info.symbol, index_info.exchange, Interval.DAILY)
if newest_bar is None:
print('当前数据未初始化')
filling_days = (datetime.now() -
newest_bar.datetime).days + 3 # 需要补齐数据的天数
ds = DataSource()
if index_info.cal_close:
# 保存最近收盘数据
ds.save_bar_data(index_info.symbol, index_info.alias, filling_days)
if index_info.cal_finance:
# 保存最近金融相关数据
trade_dates = [
bar.datetime for bar in database_manager.load_bar_data(
index_info.symbol, index_info.exchange, Interval.DAILY,
datetime.now() -
timedelta(days=filling_days), datetime.now())
]
ds.save_index_finance(trade_dates=trade_dates,
index_code=index_info.index_code)
def load_bar(
self,
vt_symbol: str,
days: int,
interval: Interval,
callback: Callable[[BarData], None]
):
""""""
symbol, exchange = extract_vt_symbol(vt_symbol)
end = datetime.now()
start = end - timedelta(days)
# Query bars from RQData by default, if not found, load from database.
bars = self.query_bar_from_rq(symbol, exchange, interval, start, end)
if not bars:
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
for bar in bars:
callback(bar)
def train():
optimizer = tf.keras.optimizers.Adam(tf.keras.optimizers.schedules.ExponentialDecay(1e-3, decay_steps = 60000, decay_rate = 0.5));
predictor = PositionPredictor(10);
checkpoint = tf.train.Checkpoint(model = predictor, optimizer = optimizer);
checkpoint.restore(tf.train.latest_checkpoint('checkpoints'));
bars = database_manager.load_bar_data('IF88', Exchange.CFFEX, Interval.MINUTE, datetime(2009,1,1), datetime(2020,8,8));
mu = 1000000 / 300; # how many possible positions
delta = 0.5 / 10000; # rate
F_tm1 = tf.zeros((1,1), dtype = tf.float32);
history_length = len(bars);
r = [bars[i].close_price - bars[i-1].close_price for i in range(1, len(bars))]; # r.shape = (history_length - 1,)
for i in range(100):
R = list();
with tf.GradientTape() as tape:
for i in range(len(r) - 11 + 1):
xt = tf.concat([tf.ones((1,1), dtype = tf.float32), tf.expand_dims(r[i:i+11], axis = 0), F_tm1], axis = -1); # xt.shape = (1, 13)
F_t = predictor(xt); # F_t.shape = (1, 1)
R.append(mu * (F_tm1 * r[i] - delta * tf.math.abs(F_t - F_tm1)));
F_tm1 = F_t;
sharpe_rate = tf.math.reduce_mean(R) / tf.math.sqrt(tf.math.reduce_mean(tf.math.square(R)) - tf.math.square(tf.math.reduce_mean(R)));
loss = -sharpe_rate;
grads = tape.gradient(loss, predictor.trainable_variables);
optimizer.apply_gradients(zip(grads, predictor.trainable_variables));
print('#%d sharpe rate: %f' % (optimizer.iterations, sharpe_rate));
checkpoint.save(join('checkpoints', 'ckpt'));
predictor.save_weights('weights.h5');
def update_all(self, symbol, exchange, trade_datas, start, end=None):
self._symbol = symbol
self._exchange = exchange
self._start = start
interval = self._interval
tp = self.interval2timdelta(self._interval)
backward_n = max(60 * tp, dt.timedelta(hours=25))
end = start + backward_n if end is None else end
history_data = database_manager.load_bar_data(symbol,
exchange,
interval,
start=start,
end=end)
self.trade_datas = trade_datas
if len(history_data) > 0 and len(history_data) / (
(end - start).total_seconds() / 60) > 0.7:
self.chart.update_all(history_data, trade_datas, [])
else:
req = HistoryRequest(symbol, exchange, start, end, interval)
gateway = self.main_engine.get_gateway('IB')
if gateway and gateway.api.status:
self.history_data = history_data = gateway.query_history(req)
self.chart.update_all(history_data, trade_datas, [])
database_manager.save_bar_data(history_data)
if len(getattr(self, 'history_data', [])) > 0:
self._end = self.history_data[-1].datetime
def load_bar(self, vt_symbol: str, days: int,
interval: Interval) -> List[BarData]:
""""""
symbol, exchange = extract_vt_symbol(vt_symbol)
end = datetime.now(get_localzone())
start = end - timedelta(days)
contract: ContractData = self.main_engine.get_contract(vt_symbol)
data = []
# Query bars from gateway if available
if contract and contract.history_data:
req = HistoryRequest(symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end)
data = self.main_engine.query_history(req, contract.gateway_name)
# Try to query bars from RQData, if not found, load from database.
else:
data = self.query_bar_from_rq(symbol, exchange, interval, start,
end)
if not data:
data = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
return data
def load_bar_data(vt_symbol: str, interval: Interval, start: datetime,
end: datetime):
""""""
symbol, exchange = extract_vt_symbol(vt_symbol)
return database_manager.load_bar_data(symbol, exchange, interval, start,
end)
def plot_bar(symbol="AG2007",
exchange=Exchange.SHFE,
interval=Interval.MINUTE,
start=datetime(2019, 4, 1),
end=datetime(2020, 10, 30),
label_count=15,
fig_size=(16, 6),
label_rotation=15,
time_format='%Y-%m-%d %H:%M:%S'):
# Load history data
bars = database_manager.load_bar_data(symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end)
# Generate x, y
x = [bar.datetime for bar in bars]
y = [bar.close_price for bar in bars]
# Show plot
y_len = len(y)
xticks = list(range(0, y_len, y_len // label_count))
xlabels = [x[_].strftime(time_format) for _ in xticks]
fig, ax = plt.subplots(figsize=fig_size)
ax.set_xticks(xticks)
ax.set_xticklabels(xlabels, rotation=label_rotation)
plt.plot(y)
plt.title(
f"{symbol} {interval.value} {min(x).strftime(time_format)}~{max(x).strftime(time_format)}"
)
plt.legend([symbol])
plt.show()
def check_update_all(self):
"""
这个方法太慢了，不建议调用。
这个方法用于本地数据库已经建立，但可能有部分数据缺失时使用
使用tushare检查更新所有的A股股票全市场日线数据
检查哪一个交易日的数据是缺失的，补全它
检查上市后是否每个交易日都有数据，若存在某一交易日无数据，尝试从tushare查询该日数据，若仍无，则说明当天停盘
:return:
"""
log.info("开始检查更新所有的A股股票全市场日线数据")
if self.symbols is not None:
with tqdm(total=len(self.symbols)) as pbar:
for tscode, list_date in zip(self.symbols['ts_code'],
self.symbols['list_date']):
pbar.set_description_str("正在检查A股日线数据，股票代码:" + tscode)
symbol, exchange = to_split_ts_codes(tscode)
local_bar = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=Interval.DAILY,
start=datetime.strptime(list_date, TS_DATE_FORMATE),
end=datetime.now())
local_bar_dates = [
bar.datetime.strftime(TS_DATE_FORMATE)
for bar in local_bar
]
index = (self.trade_cal[exchange.value][(
self.trade_cal[exchange.value].cal_date == list_date)])
trade_cal = self.trade_cal[
exchange.value].iloc[index.index[0]:]
for trade_date in trade_cal['cal_date']:
if trade_date not in local_bar_dates:
req = HistoryRequest(symbol=symbol,
exchange=exchange,
start=datetime.strptime(
trade_date,
TS_DATE_FORMATE),
end=datetime.strptime(
trade_date,
TS_DATE_FORMATE),
interval=Interval.DAILY)
bardata = self.tushare_client.query_history(
req=req)
if bardata:
log.info(tscode + "本地数据库缺失：" + trade_date)
try:
database_manager.save_bar_data(bardata)
except Exception as ex:
log.error(tscode + "数据存入数据库异常")
log.error(ex)
traceback.print_exc()
pbar.update(1)
log.info(pbar.desc)
log.info("A股股票全市场日线数据检查更新完毕")
def load_bar_data(self, symbol: str, exchange: Exchange,
interval: Interval, start: datetime,
end: datetime) -> List[BarData]:
""""""
bars = database_manager.load_bar_data(symbol, exchange, interval,
start, end)
return bars
def load_bar_data(
spread: SpreadData,
interval: Interval,
start: datetime,
end: datetime,
pricetick: float = 0
):
""""""
# Load bar data of each spread leg
leg_bars: Dict[str, Dict] = {}
for vt_symbol in spread.legs.keys():
symbol, exchange = extract_vt_symbol(vt_symbol)
bar_data: List[BarData] = database_manager.load_bar_data(
symbol, exchange, interval, start, end
)
bars: Dict[datetime, BarData] = {bar.datetime: bar for bar in bar_data}
leg_bars[vt_symbol] = bars
# Calculate spread bar data
spread_bars: List[BarData] = []
for dt in bars.keys():
spread_price = 0
spread_value = 0
spread_available = True
for leg in spread.legs.values():
leg_bar = leg_bars[leg.vt_symbol].get(dt, None)
if leg_bar:
price_multiplier = spread.price_multipliers[leg.vt_symbol]
spread_price += price_multiplier * leg_bar.close_price
spread_value += abs(price_multiplier) * leg_bar.close_price
else:
spread_available = False
if spread_available:
if pricetick:
spread_price = round_to(spread_price, pricetick)
spread_bar = BarData(
symbol=spread.name,
exchange=exchange.LOCAL,
datetime=dt,
interval=interval,
open_price=spread_price,
high_price=spread_price,
low_price=spread_price,
close_price=spread_price,
gateway_name="SPREAD",
)
spread_bar.value = spread_value
spread_bars.append(spread_bar)
return spread_bars
def main(symbol, exchange, start, end):
# 1) prepare observation X
data = database_manager.load_bar_data(symbol, exchange, Interval.MINUTE, start, end);
if len(data) == 0:
# download data if not presented
if not tsdata_client.inited:
print('登录tushare');
succeed = tsdata_client.init();
if False == succeed:
print('tushare登录失败');
return;
req = HistoryRequest(symbol = symbol, exchange = exchange, interval = Interval.MINUTE, start = start, end = end);
data = tsdata_client.query_history(req);
database_manager.save_bar_data(data);
data = database_manager.load_bar_data(symbol, exchange, Interval.MINUTE, start, end);
X = [[log(data[i].close_price) - log(data[i-1].close_price),
log(data[i].close_price) - log(data[i-5].close_price),
log(data[i].high_price) - log(data[i].low_price)] for i in range(5, len(data))]; # X.shape = (len(data) - 5, 3)
# 2) learn the HMM model
hmm = GaussianHMM(n_components = 6, covariance_type = 'diag', n_iter = 5000).fit(X);
print('hidden markov model %s converged' % ('is' if hmm.monitor_.converged else 'is not'));
with open('hmm.pkl', 'wb') as f:
pickle.dump(hmm, f);
# 3) visualize
latent_states_sequence = hmm.predict(X);
plt.figure(figsize = (15,8));
dates = [data[i].datetime.strftime('%Y-%m-%d') for i in range(5, len(data))];
close_prices = [data[i].close_price for i in range(5, len(data))];
for i in range(hmm.n_components):
idx = (latent_states_sequence == i); # index of day labeled with i
plt.plot(np.array(dates)[idx], np.array(close_prices)[idx], '.', label = 'latent idx %d' % i, lw = 1);
plt.legend();
plt.grid(1);
plt.axis([0, len(close_prices), min(close_prices), max(close_prices)]);
plt.savefig('colored_k_bar.png');
plt.show();
for i in range(hmm.n_components):
idx = (latent_states_sequence == i); # index of day labeled with i
idx = np.append(False, idx[:-1]); # index of the next day of the day labeled with i, because if you trade on day with label i the reward comes one day after
plt.plot(np.exp(np.array(X)[idx, 0].cumsum()), label = 'latent_state %d' % i);
plt.legend();
plt.grid(1);
plt.savefig('return_curve.png');
plt.show();
def load_history_data():
symbol = 'rb1910'
exchange = Exchange.SHFE
interval = Interval.MINUTE
start = datetime(2019, 7, 10)
end = datetime.now()
return database_manager.load_bar_data(symbol, exchange, interval, start,
end)
def load_data(vt_symbol: str, interval: str, start: datetime,
end: datetime) -> pd.DataFrame:
symbol, exchange = extract_vt_symbol(vt_symbol)
data = database_manager.load_bar_data(
symbol,
exchange,
Interval(interval),
start=start,
end=end,
)
return vt_bar_to_df(data)
def load_bar_data(
symbol: str,
exchange: Exchange,
interval: Interval,
start: datetime,
end: datetime
):
""""""
return database_manager.load_bar_data(
symbol, exchange, interval, start, end
)
def load_bar_data(
symbol: str,
exchange: Exchange,
interval: Interval,
start: datetime,
end: datetime,
collection_name:str = None
):
""""""
return database_manager.load_bar_data(
symbol, exchange, interval, start, end, collection_name = collection_name
)
def get_newest_bar_data(self, symbol: str, exchange: Exchange,
interval: Interval) -> BarData or None:
""""""
for overview in self.bar_overviews:
if exchange == overview.exchange and interval == overview.interval and symbol == overview.symbol:
bars = database_manager.load_bar_data(symbol=symbol,
exchange=exchange,
interval=interval,
start=overview.start,
end=overview.start)
return bars[0] if bars is not None else None
return None
def query_history(self, req: HistoryRequest):
"""
Query history bar data from RQData.
"""
symbol = req.symbol
exchange = req.exchange
interval = req.interval
start = req.start
end = req.end
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
if not bars:
self.download_bar(symbol=symbol,
exchange=exchange,
interval=interval,
start_dt=start,
end_dt=end)
self.data_csv2db(symbol=symbol,
exchange=exchange,
interval=interval,
start_dt=start,
end_dt=end)
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
return bars
def test_init(self):
symbol, alias = '000042', 'XSHG'
ds = DataSource(mode='remote')
ds.save_bar_data(symbol, alias)
bar_datas = database_manager.load_bar_data(
symbol, const.Exchange.get_exchange_by_alias(alias),
const.Interval.DAILY, datetime(2010, 1, 1), datetime.now())
finance_datas = []
for bar in bar_datas:
finance_data = ds.get_index_finance(bar.datetime,
symbol + '.' + alias)
finance_datas.append(finance_data)
if len(finance_datas) == 20:
database_manager.save_finance_data(finance_datas)
finance_datas.clear()
def load_bar_data(self,
symbol,
alias,
start_date: datetime = None,
end_data: datetime = None):
"""取出bar数据"""
exchange = const.Exchange.get_exchange_by_alias(alias)
interval = const.Interval.DAILY
progress_delta = timedelta(days=30)
total_delta = end_data - start_date
interval_delta = INTERVAL_DELTA_MAP[interval]
start = start_date
end = start_date + progress_delta
progress = 0
df = pd.DataFrame(columns=('date', 'open', 'high', 'low', 'close',
'volume'))
while start < end_data:
end = min(end,
end_data) # Make sure end time stays within set range
datas = database_manager.load_bar_data(symbol, exchange, interval,
start, end)
# data转为dataframe数据
for i, data in enumerate(datas):
df = df.append(
{
'date': data.datetime,
'open': data.open_price,
'high': data.high_price,
'low': data.low_price,
'close': data.close_price,
'volume': data.volume
},
ignore_index=True)
progress += progress_delta / total_delta
progress = min(progress, 1)
progress_bar = "#" * int(progress * 10)
print(f"加载进度：{progress_bar} [{progress:.0%}]")
start = end + interval_delta
end += (progress_delta + interval_delta)
print(f"历史数据加载完成，数据量：{df.__len__()}")
return df
def update_backward_bars(self, n):
chart = self.chart
last_bar = chart._manager.get_bar(chart.last_ix)
if last_bar:
symbol = last_bar.symbol
exchange = last_bar.exchange
if self._end:
start = max(last_bar.datetime, self._end)
else:
start = last_bar.datetime
if start >= dt.datetime.now(get_localzone()):
return
tp = self.interval2timdelta(self._interval)
backward_n = max(tp * n, dt.timedelta(minutes=60))
end = start + backward_n
if not self.checkTradeTime(end.time()):
history_data = database_manager.load_bar_data(symbol,
exchange,
self._interval,
start=start,
end=end)
if len(history_data) == 0 or len(history_data) / (
(end - start).total_seconds() / 60) < 0.7:
req = HistoryRequest(symbol, exchange, start, end,
self._interval)
gateway = self.main_engine.get_gateway('IB')
if gateway and gateway.api.status:
history_data = gateway.query_history(req)
database_manager.save_bar_data(history_data)
for bar in history_data:
self.chart.update_bar(bar)
last_bar_after_update = chart._manager.get_bar(chart.last_ix)
self.chart.clear_trades()
self.chart.update_trades([
t for t in self.trade_datas
if t.datetime <= last_bar_after_update.datetime
])
self.chart.update_pos()
self.chart.update_pnl()
self._end = end
def load_bar(
self,
vt_symbol: str,
days: int,
interval: Interval,
callback: Callable[[BarData], None],
use_database: bool
):
""""""
symbol, exchange = extract_vt_symbol(vt_symbol)
end = datetime.now()
start = end - timedelta(days)
bars = []
# Pass gateway and RQData if use_database set to True
#如果database设置为foalse，就先从rqdata里面取数，如果里面没有再从数据库里面查找有
#没有相关数据
if not use_database:
# Query bars from gateway if available
contract = self.main_engine.get_contract(vt_symbol)##什么意思
if contract and contract.history_data:
req = HistoryRequest(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end
)
bars = self.main_engine.query_history(req, contract.gateway_name)
# Try to query bars from RQData, if not found, load from database.
else:
bars = self.query_bar_from_rq(symbol, exchange, interval, start, end)
#从数据库中提取数据
if not bars:
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
for bar in bars:
callback(bar)
def load_bar(
self,
vt_symbol: str,
days: int,
interval: Interval,
callback: Callable[[BarData], None],
use_database: bool
):
""""""
symbol, exchange = extract_vt_symbol(vt_symbol)
end = datetime.now(get_localzone())
end = datetime(year=end.year, month=end.month, day=end.day, hour=end.hour, minute=0)
start = end - timedelta(days)
bars = []
# Pass gateway and RQData if use_database set to True
if not use_database:
# Query bars from gateway if available
contract = self.main_engine.get_contract(vt_symbol)
if contract and contract.history_data:
req = HistoryRequest(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end
)
bars = self.main_engine.query_history(req, contract.gateway_name)
# Try to query bars from RQData, if not found, load from database.
else:
bars = self.query_bar_from_rq(symbol, exchange, interval, start, end)
if not bars:
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
for bar in bars:
callback(bar)
def load_bar(self, vt_symbol: str, days: int, interval: Interval,
callback: Callable[[BarData], None], use_database: bool):
""""""
symbol, exchange = extract_vt_symbol(vt_symbol)
end = datetime.now()
start = end - timedelta(days)
bars = []
data_source = ""
# Pass gateway and RQData if use_database set to True
if not use_database:
# Query bars from gateway if available
contract = self.main_engine.get_contract(vt_symbol)
if contract and contract.history_data:
data_source = "行情服务器"
req = HistoryRequest(symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end)
bars = self.main_engine.query_history(req,
contract.gateway_name)
# Try to query bars from RQData, if not found, load from database.
else:
data_source = "tdx数据源"
bars = self.query_bar_from_rq(symbol, exchange, interval,
start, end)
if not bars:
data_source = "本地数据库"
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
# JinAdd : 添加日志
self.write_log(f"从{data_source}加载{len(bars)}条数据")
for bar in bars:
callback(bar)
def visulize(self, QModelIndex):
from vnpy.trader.database import database_manager
symbol = self.trade_values[QModelIndex.row()].symbol
exchange = self.trade_values[QModelIndex.row()].exchange
trade_date: dt.date = self.daily_trade_result.name
start = dt.datetime(trade_date.year, trade_date.month, trade_date.day)
end = dt.datetime(trade_date.year, trade_date.month, trade_date.day,
23, 59)
history = database_manager.load_bar_data(symbol, exchange,
Interval.MINUTE, start, end)
tradeData = [t for t in self.trade_values if t.symbol == symbol]
chart = TradeResultVisulizationChart(
history,
tradeData,
title=f"{self.daily_trade_result.name}交易行情",
parent=self.parent())
chart.exec_()
def load_symbol_data(vt_symbol, start, end):
"""
从数据库读取数据
:param vt_symbol:
:param start:
:param end:
:return:
"""
symbol, exchange = extract_vt_symbol(vt_symbol) # XBTUSD.BITMEX 分离
start = datetime.strptime(start, "%Y%m%d")
end = datetime.strptime(end, "%Y%m%d")
interval = Interval.MINUTE
data = database_manager.load_bar_data(symbol, exchange, interval, start,
end) # 数据库读取数据
dt_list = []
close_list = []
for bar in data:
dt_list.append(bar.datetime)
close_list.append(bar.close_price)
s = pd.Series(close_list, index=dt_list)
return s
def load_bar(self, vt_symbol: str, days: int, interval: Interval,
callback: Callable[[BarData], None]):
"""载入历史bar"""
symbol, exchange = extract_vt_symbol(vt_symbol)
end = datetime.now()
start = end - timedelta(days)
# Query bars from RQData by default, if not found, load from database.
# TODO
# 这里CTA的载入历史数据是从米匡那里拿，这个必须修改，没有米匡账号！
# 初步建议修改为在主引擎中发送query_history拿数据，由gateway回调数据
# OKEX的历史数据由OKEX提供，FUTURES的历史数据由数据库提供，每个都不一样，因此，不能在这里统一，要改成在gaetway中分发
bars = self.query_bar_from_rq(symbol, exchange, interval, start, end)
if not bars:
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=interval,
start=start,
end=end,
)
for bar in bars:
callback(bar)
def _query_history(self, vt_symbol: str, interval: Interval,
start: datetime, end: datetime) -> None:
""""""
contract: ContractData = self.main_engine.get_contract(vt_symbol)
req = HistoryRequest(symbol=contract.symbol,
exchange=contract.exchange,
interval=interval,
start=start,
end=end)
if contract.history_data:
data = self.main_engine.query_history(req, contract.gateway_name)
else:
data = rqdata_client.query_history(req)
if not data:
data = database_manager.load_bar_data(symbol=contract.symbol,
exchange=contract.exchange,
interval=interval,
start=start,
end=end)
event = Event(EVENT_CHART_HISTORY, data)
self.event_engine.put(event)
def market_open(self):
# 读一下前几天的日内收益率数据，算峰度
bars = []
# 回测时自带
if self.cta_engine.engine_type == EngineType.BACKTESTING:
symbol = self.cta_engine.symbol
exchange = self.cta_engine.exchange
end = self.cta_engine.datetime - timedelta(1)
start = end - timedelta(30)
# 实盘时
else:
symbol, exchange = self.cta_engine.extract_vt_symbol(self.vt_symbol)
end = datetime.now()
start = end - timedelta(30)
# 在线数据源获取
bars = self.cta_engine.query_bar_from_rq(symbol, exchange, Interval.DAILY, start, end)
# 没有的话问本地数据库要
if not bars:
bars = database_manager.load_bar_data(
symbol=symbol,
exchange=exchange,
interval=Interval.DAILY,
start=start,
end=end,
)
# Generate history data in DataFrame
df = pd.DataFrame()
t = []
o = []
h = []
l = []
c = []
v = []
for i in range(0,len(bars)):
time = bars[i].datetime
open_price = bars[i].open_price
high_price = bars[i].high_price
low_price = bars[i].low_price
close_price = bars[i].close_price
volume = bars[i].volume
t.append(time)
o.append(open_price)
h.append(high_price)
l.append(low_price)
c.append(close_price)
v.append(volume)
df["open"] = o
df["high"] = h
df["low"] = l
df["close"] = c
df["volume"] = v
df["time"] = t
df["intraday_return"] = np.log(df["close"]/df["open"])
kurt_array = df["intraday_return"].rolling(self.kurt_len).kurt().tolist()
kurt_value = 0
if len(kurt_array) >= 1:
kurt_value = kurt_array[-1]
self.write_log(f"近{self.kurt_len}日日内峰度{kurt_value}，阈值{self.kurt_filter}")
if kurt_value < self.kurt_filter:
self.cannot_kurt = 1
else:
self.cannot_kurt = 0
from vnpy.trader.ui import create_qapp, QtCore
from vnpy.trader.database import database_manager
from vnpy.trader.constant import Exchange, Interval
from vnpy.chart import ChartWidget, VolumeItem, CandleItem
from vnpy.trader.object import BarData
from random import randint
import pandas as pd
"""
"""
if __name__ == "__main__":
app = create_qapp()
bars = database_manager.load_bar_data("IF88",
Exchange.CFFEX,
interval=Interval.MINUTE,
start=datetime(2019, 7, 1),
end=datetime(2019, 7, 17))
"""
symbol: str
exchange: Exchange
datetime: datetime
interval: Interval = None
volume: float = 0
open_interest: float = 0
open_price: float = 0
high_price: float = 0
low_price: float = 0
close_price: float = 0
"""
