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optimize performance of resam data in rule_strategy & exchange

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bxdd
2021-07-01 14:35:49 +00:00
parent b242d6e1e1
commit 8b85b9eee7
3 changed files with 65 additions and 23 deletions
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25
qlib/backtest/exchange.py
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@@ -12,7 +12,7 @@ import pandas as pd
from ..data.data import D
from ..data.dataset.utils import get_level_index
from ..config import C, REG_CN
from ..utils.resam import resam_ts_data
from ..utils.resam import resam_ts_data, ts_data_last
from ..log import get_module_logger
from .order import Order
@@ -166,7 +166,7 @@ class Exchange:
quote_dict = {}
for stock_id, stock_val in quote_df.groupby(level="instrument"):
quote_dict[stock_id] = stock_val
quote_dict[stock_id] = stock_val.droplevel(level="instrument")
self.quote = quote_dict
@@ -186,13 +186,13 @@ class Exchange:
"""
if direction is None:
buy_limit = resam_ts_data(self.quote[stock_id]["limit_buy"], start_time, end_time, method="all").iloc[0]
sell_limit = resam_ts_data(self.quote[stock_id]["limit_sell"], start_time, end_time, method="all").iloc[0]
buy_limit = resam_ts_data(self.quote[stock_id]["limit_buy"], start_time, end_time, method="all")
sell_limit = resam_ts_data(self.quote[stock_id]["limit_sell"], start_time, end_time, method="all")
return buy_limit or sell_limit
elif direction == Order.BUY:
return resam_ts_data(self.quote[stock_id]["limit_buy"], start_time, end_time, method="all").iloc[0]
return resam_ts_data(self.quote[stock_id]["limit_buy"], start_time, end_time, method="all")
elif direction == Order.SELL:
return resam_ts_data(self.quote[stock_id]["limit_sell"], start_time, end_time, method="all").iloc[0]
return resam_ts_data(self.quote[stock_id]["limit_sell"], start_time, end_time, method="all")
else:
raise ValueError(f"direction {direction} is not supported!")
@@ -267,16 +267,16 @@ class Exchange:
)
def get_quote_info(self, stock_id, start_time, end_time):
return resam_ts_data(self.quote[stock_id], start_time, end_time, method="last").iloc[0]
return resam_ts_data(self.quote[stock_id], start_time, end_time, method=ts_data_last)
def get_close(self, stock_id, start_time, end_time):
return resam_ts_data(self.quote[stock_id]["$close"], start_time, end_time, method="last").iloc[0]
return resam_ts_data(self.quote[stock_id]["$close"], start_time, end_time, method=ts_data_last)
def get_volume(self, stock_id, start_time, end_time):
return resam_ts_data(self.quote[stock_id]["$volume"], start_time, end_time, method="sum").iloc[0]
return resam_ts_data(self.quote[stock_id]["$volume"], start_time, end_time, method="sum")
def get_deal_price(self, stock_id, start_time, end_time):
deal_price = resam_ts_data(self.quote[stock_id][self.deal_price], start_time, end_time, method="last").iloc[0]
deal_price = resam_ts_data(self.quote[stock_id][self.deal_price], start_time, end_time, method=ts_data_last)
if np.isclose(deal_price, 0.0) or np.isnan(deal_price):
self.logger.warning(
f"(stock_id:{stock_id}, trade_time:{(start_time, end_time)}, {self.deal_price}): {deal_price}!!!"
@@ -295,10 +295,7 @@ class Exchange:
"""
if stock_id not in self.quote:
return None
res = resam_ts_data(self.quote[stock_id]["$factor"], start_time, end_time, method="last")
if res is not None:
res = res.iloc[0]
return res
return resam_ts_data(self.quote[stock_id]["$factor"], start_time, end_time, method=ts_data_last)
def generate_amount_position_from_weight_position(self, weight_position, cash, start_time, end_time):
"""