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black format & add comments & add randStrategy direction

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This commit is contained in:
Young
2021-06-28 08:16:51 +00:00
committed by you-n-g
parent 72c9593aa7
commit 27f0db669f
13 changed files with 132 additions and 102 deletions
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69
qlib/backtest/__init__.py
View File

@@ -92,7 +92,9 @@ def get_exchange(
return init_instance_by_config(exchange, accept_types=Exchange) return init_instance_by_config(exchange, accept_types=Exchange)
def create_account_instance(start_time, end_time, benchmark: str, account: float, pos_type: str="Position") -> Account: def create_account_instance(
start_time, end_time, benchmark: str, account: float, pos_type: str = "Position"
) -> Account:
""" """
# TODO: is very strange pass benchmark_config in the account(maybe for report) # TODO: is very strange pass benchmark_config in the account(maybe for report)
# There should be a post-step to process the report. # There should be a post-step to process the report.
@@ -119,26 +121,25 @@ def create_account_instance(start_time, end_time, benchmark: str, account: float
"start_time": start_time, "start_time": start_time,
"end_time": end_time, "end_time": end_time,
}, },
"pos_type": pos_type "pos_type": pos_type,
} }
return Account(**kwargs) return Account(**kwargs)
def get_strategy_executor(start_time, def get_strategy_executor(
end_time, start_time,
strategy: BaseStrategy, end_time,
executor: BaseExecutor, strategy: BaseStrategy,
benchmark: str = "SH000300", executor: BaseExecutor,
account: Union[float, str] = 1e9, benchmark: str = "SH000300",
exchange_kwargs: dict = {}, account: Union[float, str] = 1e9,
pos_type: str = "Position", exchange_kwargs: dict = {},
): pos_type: str = "Position",
):
trade_account = create_account_instance(start_time=start_time, trade_account = create_account_instance(
end_time=end_time, start_time=start_time, end_time=end_time, benchmark=benchmark, account=account, pos_type=pos_type
benchmark=benchmark, )
account=account,
pos_type=pos_type)
exchange_kwargs = copy.copy(exchange_kwargs) exchange_kwargs = copy.copy(exchange_kwargs)
if "start_time" not in exchange_kwargs: if "start_time" not in exchange_kwargs:
@@ -154,14 +155,16 @@ def get_strategy_executor(start_time,
return trade_strategy, trade_executor return trade_strategy, trade_executor
def backtest(start_time, def backtest(
end_time, start_time,
strategy, end_time,
executor, strategy,
benchmark="SH000300", executor,
account=1e9, benchmark="SH000300",
exchange_kwargs={}, account=1e9,
pos_type: str = "Position"): exchange_kwargs={},
pos_type: str = "Position",
):
trade_strategy, trade_executor = get_strategy_executor( trade_strategy, trade_executor = get_strategy_executor(
start_time, start_time,
@@ -178,14 +181,16 @@ def backtest(start_time,
return report_dict, indicator_dict return report_dict, indicator_dict
def collect_data(start_time, def collect_data(
end_time, start_time,
strategy, end_time,
executor, strategy,
benchmark="SH000300", executor,
account=1e9, benchmark="SH000300",
exchange_kwargs={}, account=1e9,
pos_type: str = "Position"): exchange_kwargs={},
pos_type: str = "Position",
):
trade_strategy, trade_executor = get_strategy_executor( trade_strategy, trade_executor = get_strategy_executor(
start_time, start_time,

18
qlib/backtest/account.py
View File

@@ -63,7 +63,9 @@ class AccumulatedInfo:
class Account: class Account:
def __init__(self, init_cash: float=1e9, freq: str = "day", benchmark_config: dict = {}, pos_type:str = "Position"): def __init__(
self, init_cash: float = 1e9, freq: str = "day", benchmark_config: dict = {}, pos_type: str = "Position"
):
self.pos_type = pos_type self.pos_type = pos_type
self.init_vars(init_cash, freq, benchmark_config) self.init_vars(init_cash, freq, benchmark_config)
@@ -71,13 +73,13 @@ class Account:
# init cash # init cash
self.init_cash = init_cash self.init_cash = init_cash
self.current: BasePosition = init_instance_by_config({ self.current: BasePosition = init_instance_by_config(
'class': self.pos_type, {
'kwargs': { "class": self.pos_type,
"cash": init_cash "kwargs": {"cash": init_cash},
}, "module_path": "qlib.backtest.position",
'module_path': "qlib.backtest.position", }
}) )
self.accum_info = AccumulatedInfo() self.accum_info = AccumulatedInfo()
self.reset(freq=freq, benchmark_config=benchmark_config, init_report=True) self.reset(freq=freq, benchmark_config=benchmark_config, init_report=True)

6
qlib/backtest/backtest.py
View File

@@ -23,7 +23,9 @@ def backtest_loop(start_time, end_time, trade_strategy: BaseStrategy, trade_exec
return return_value.get("report"), return_value.get("indicator") return return_value.get("report"), return_value.get("indicator")
def collect_data_loop(start_time, end_time, trade_strategy: BaseStrategy, trade_executor: BaseExecutor, return_value: dict = None): def collect_data_loop(
start_time, end_time, trade_strategy: BaseStrategy, trade_executor: BaseExecutor, return_value: dict = None
):
"""Generator for collecting the trade decision data for rl training """Generator for collecting the trade decision data for rl training
Parameters Parameters
@@ -68,7 +70,7 @@ def collect_data_loop(start_time, end_time, trade_strategy: BaseStrategy, trade_
} }
all_indicators = {} all_indicators = {}
for _executor in all_executors: for _executor in all_executors:
key = "{}{}".format( *Freq.parse(_executor.time_per_step)) key = "{}{}".format(*Freq.parse(_executor.time_per_step))
all_indicators[key] = _executor.get_trade_indicator().generate_trade_indicators_dataframe() all_indicators[key] = _executor.get_trade_indicator().generate_trade_indicators_dataframe()
all_indicators[key + "_obj"] = _executor.get_trade_indicator() all_indicators[key + "_obj"] = _executor.get_trade_indicator()
return_value.update({"report": all_reports, "indicator": all_indicators}) return_value.update({"report": all_reports, "indicator": all_indicators})

9
qlib/backtest/order.py
View File

@@ -2,8 +2,10 @@
# Licensed under the MIT License. # Licensed under the MIT License.
# TODO: rename it with decision.py # TODO: rename it with decision.py
from __future__ import annotations from __future__ import annotations
# try to fix circular imports when enabling type hints # try to fix circular imports when enabling type hints
from typing import TYPE_CHECKING from typing import TYPE_CHECKING
if TYPE_CHECKING: if TYPE_CHECKING:
from qlib.strategy.base import BaseStrategy from qlib.strategy.base import BaseStrategy
from qlib.backtest.utils import TradeCalendarManager from qlib.backtest.utils import TradeCalendarManager
@@ -59,6 +61,7 @@ class BaseTradeDecision:
1. The outer strategy's decision is available at the start of the interval 1. The outer strategy's decision is available at the start of the interval
2. Same as `case 1.3` 2. Same as `case 1.3`
""" """
def __init__(self, strategy: BaseStrategy): def __init__(self, strategy: BaseStrategy):
""" """
Parameters Parameters
@@ -125,7 +128,8 @@ class TradeDecisionWO(BaseTradeDecision):
Trade Decision (W)ith (O)rder. Trade Decision (W)ith (O)rder.
Besides, the time_range is also included. Besides, the time_range is also included.
""" """
def __init__(self, order_list: List[Order], strategy: BaseStrategy, idx_range: Tuple=None):
def __init__(self, order_list: List[Order], strategy: BaseStrategy, idx_range: Tuple = None):
super().__init__(strategy) super().__init__(strategy)
self.order_list = order_list self.order_list = order_list
self.idx_range = idx_range self.idx_range = idx_range
@@ -198,8 +202,7 @@ class TradeDecisionWithOrderPool:
class BaseDecisionUpdater: class BaseDecisionUpdater:
def update_decision(self, decision, trade_calendar) -> BaseTradeDecision: def update_decision(self, decision, trade_calendar) -> BaseTradeDecision:
"""[summary] """
Parameters Parameters
---------- ----------
decision : BaseTradeDecision decision : BaseTradeDecision

9
qlib/backtest/position.py
View File

@@ -15,7 +15,8 @@ class BasePosition:
The Position want to maintain the position like a dictionary The Position want to maintain the position like a dictionary
Please refer to the `Position` class for the position Please refer to the `Position` class for the position
""" """
def __init__(self, cash=0., *args, **kwargs) -> None:
def __init__(self, cash=0.0, *args, **kwargs) -> None:
pass pass
def skip_update(self) -> bool: def skip_update(self) -> bool:
@@ -46,7 +47,6 @@ class BasePosition:
""" """
raise NotImplementedError(f"Please implement the `check_stock` method") raise NotImplementedError(f"Please implement the `check_stock` method")
def update_order(self, order: Order, trade_val: float, cost: float, trade_price: float): def update_order(self, order: Order, trade_val: float, cost: float, trade_price: float):
""" """
Parameters Parameters
@@ -86,6 +86,7 @@ class BasePosition:
the value(money) of all the stock the value(money) of all the stock
""" """
raise NotImplementedError(f"Please implement the `calculate_stock_value` method") raise NotImplementedError(f"Please implement the `calculate_stock_value` method")
def get_stock_list(self) -> List: def get_stock_list(self) -> List:
""" """
Get the list of stocks in the position. Get the list of stocks in the position.
@@ -140,7 +141,7 @@ class BasePosition:
""" """
raise NotImplementedError(f"Please implement the `get_stock_amount_dict` method") raise NotImplementedError(f"Please implement the `get_stock_amount_dict` method")
def get_stock_weight_dict(self, only_stock: bool=False) -> Dict: def get_stock_weight_dict(self, only_stock: bool = False) -> Dict:
""" """
generate stock weight dict {stock_id : value weight of stock in the position} generate stock weight dict {stock_id : value weight of stock in the position}
it is meaningful in the beginning or the end of each trade date it is meaningful in the beginning or the end of each trade date
@@ -399,13 +400,13 @@ class Position(BasePosition):
self.position["now_account_value"] = now_account_value self.position["now_account_value"] = now_account_value
class InfPosition(BasePosition): class InfPosition(BasePosition):
""" """
Position with infinite cash and amount. Position with infinite cash and amount.
This is useful for generating random orders. This is useful for generating random orders.
""" """
def skip_update(self) -> bool: def skip_update(self) -> bool:
""" Updating state is meaningless for InfPosition """ """ Updating state is meaningless for InfPosition """
return True return True

5
qlib/backtest/report.py
View File

@@ -18,7 +18,7 @@ from ..tests.config import CSI300_BENCH
class Report: class Report:
''' """
Motivation: Motivation:
Report is for supporting portfolio related metrics. Report is for supporting portfolio related metrics.
@@ -26,7 +26,8 @@ class Report:
daily report of the account daily report of the account
contain those followings: returns, costs turnovers, accounts, cash, bench, value contain those followings: returns, costs turnovers, accounts, cash, bench, value
update report update report
''' """
def __init__(self, freq: str = "day", benchmark_config: dict = {}): def __init__(self, freq: str = "day", benchmark_config: dict = {}):
""" """
Parameters Parameters

1
qlib/backtest/utils.py
View File

@@ -140,7 +140,6 @@ class BaseInfrastructure:
self.reset_infra(**infra_dict) self.reset_infra(**infra_dict)
class CommonInfrastructure(BaseInfrastructure): class CommonInfrastructure(BaseInfrastructure):
def get_support_infra(self): def get_support_infra(self):
return ["trade_account", "trade_exchange"] return ["trade_account", "trade_exchange"]

8
qlib/contrib/strategy/model_strategy.py
View File

@@ -15,6 +15,7 @@ class TopkDropoutStrategy(ModelStrategy):
# TODO: # TODO:
# 1. Supporting leverage the get_range_limit result from the decision # 1. Supporting leverage the get_range_limit result from the decision
# 2. Supporting alter_outer_trade_decision # 2. Supporting alter_outer_trade_decision
# 3. Supporting checking the availability of trade decision
def __init__( def __init__(
self, self,
model, model,
@@ -104,7 +105,7 @@ class TopkDropoutStrategy(ModelStrategy):
pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1) pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
pred_score = resam_ts_data(self.pred_scores, start_time=pred_start_time, end_time=pred_end_time, method="last") pred_score = resam_ts_data(self.pred_scores, start_time=pred_start_time, end_time=pred_end_time, method="last")
if pred_score is None: if pred_score is None:
return [] return TradeDecisionWO([], self)
if self.only_tradable: if self.only_tradable:
# If The strategy only consider tradable stock when make decision # If The strategy only consider tradable stock when make decision
# It needs following actions to filter stocks # It needs following actions to filter stocks
@@ -256,6 +257,7 @@ class WeightStrategyBase(ModelStrategy):
# TODO: # TODO:
# 1. Supporting leverage the get_range_limit result from the decision # 1. Supporting leverage the get_range_limit result from the decision
# 2. Supporting alter_outer_trade_decision # 2. Supporting alter_outer_trade_decision
# 3. Supporting checking the availability of trade decision
def __init__( def __init__(
self, self,
model, model,
@@ -332,9 +334,9 @@ class WeightStrategyBase(ModelStrategy):
pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1) pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
pred_score = resam_ts_data(self.pred_scores, start_time=pred_start_time, end_time=pred_end_time, method="last") pred_score = resam_ts_data(self.pred_scores, start_time=pred_start_time, end_time=pred_end_time, method="last")
if pred_score is None: if pred_score is None:
return [] return TradeDecisionWO([], self)
current_temp = copy.deepcopy(self.trade_position) current_temp = copy.deepcopy(self.trade_position)
assert(isinstance(current_temp, Position)) # Avoid InfPosition assert isinstance(current_temp, Position) # Avoid InfPosition
target_weight_position = self.generate_target_weight_position( target_weight_position = self.generate_target_weight_position(
score=pred_score, current=current_temp, trade_start_time=trade_start_time, trade_end_time=trade_end_time score=pred_score, current=current_temp, trade_start_time=trade_start_time, trade_end_time=trade_end_time

73
qlib/contrib/strategy/rule_strategy.py
View File

@@ -102,7 +102,7 @@ class TWAPStrategy(BaseStrategy):
trade_step = self.trade_calendar.get_trade_step() trade_step = self.trade_calendar.get_trade_step()
# get the total count of trading step # get the total count of trading step
start_idx, end_idx = get_start_end_idx(self, self.outer_trade_decision) start_idx, end_idx = get_start_end_idx(self, self.outer_trade_decision)
trade_len = end_idx - start_idx + 1 trade_len = end_idx - start_idx + 1
if trade_step < start_idx: if trade_step < start_idx:
# It is not time to start trading # It is not time to start trading
@@ -137,12 +137,16 @@ class TWAPStrategy(BaseStrategy):
# calculate the amount of one part, ceil the amount # calculate the amount of one part, ceil the amount
# floor((trade_unit_cnt + trade_len - rel_trade_step) / (trade_len - rel_trade_step + 1)) == ceil(trade_unit_cnt / (trade_len - rel_trade_step + 1)) # floor((trade_unit_cnt + trade_len - rel_trade_step) / (trade_len - rel_trade_step + 1)) == ceil(trade_unit_cnt / (trade_len - rel_trade_step + 1))
_order_amount = ( _order_amount = (
(trade_unit_cnt + trade_len - rel_trade_step - 1) // (trade_len - rel_trade_step) * _amount_trade_unit (trade_unit_cnt + trade_len - rel_trade_step - 1)
// (trade_len - rel_trade_step)
* _amount_trade_unit
) )
if order.direction == order.SELL: if order.direction == order.SELL:
# sell all amount at last # sell all amount at last
if self.trade_amount[order.stock_id] > 1e-5 and (_order_amount < 1e-5 or rel_trade_step == trade_len - 1): if self.trade_amount[order.stock_id] > 1e-5 and (
_order_amount < 1e-5 or rel_trade_step == trade_len - 1
):
_order_amount = self.trade_amount[order.stock_id] _order_amount = self.trade_amount[order.stock_id]
_order_amount = min(_order_amount, self.trade_amount[order.stock_id]) _order_amount = min(_order_amount, self.trade_amount[order.stock_id])
@@ -173,6 +177,7 @@ class SBBStrategyBase(BaseStrategy):
# TODO: # TODO:
# 1. Supporting leverage the get_range_limit result from the decision # 1. Supporting leverage the get_range_limit result from the decision
# 2. Supporting alter_outer_trade_decision # 2. Supporting alter_outer_trade_decision
# 3. Supporting checking the availability of trade decision
def __init__( def __init__(
self, self,
@@ -225,8 +230,7 @@ class SBBStrategyBase(BaseStrategy):
self.trade_trend = {} self.trade_trend = {}
self.trade_amount = {} self.trade_amount = {}
# init the trade amount of order and predicted trade trend # init the trade amount of order and predicted trade trend
outer_order_generator = outer_trade_decision.generator() for order in outer_trade_decision.get_decision():
for order in outer_order_generator:
self.trade_trend[order.stock_id] = self.TREND_MID self.trade_trend[order.stock_id] = self.TREND_MID
self.trade_amount[order.stock_id] = order.amount self.trade_amount[order.stock_id] = order.amount
@@ -248,8 +252,7 @@ class SBBStrategyBase(BaseStrategy):
pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1) pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
order_list = [] order_list = []
# for each order in in self.outer_trade_decision # for each order in in self.outer_trade_decision
outer_order_generator = self.outer_trade_decision.generator(only_enable=True) for order in self.outer_trade_decision.get_decision():
for order in outer_order_generator:
# get the price trend # get the price trend
if trade_step % 2 == 0: if trade_step % 2 == 0:
# in the first of two adjacent bars, predict the price trend # in the first of two adjacent bars, predict the price trend
@@ -379,9 +382,11 @@ class SBBStrategyEMA(SBBStrategyBase):
""" """
(S)elect the (B)etter one among every two adjacent trading (B)ars to sell or buy with (EMA) signal. (S)elect the (B)etter one among every two adjacent trading (B)ars to sell or buy with (EMA) signal.
""" """
# TODO: # TODO:
# 1. Supporting leverage the get_range_limit result from the decision # 1. Supporting leverage the get_range_limit result from the decision
# 2. Supporting alter_outer_trade_decision # 2. Supporting alter_outer_trade_decision
# 3. Supporting checking the availability of trade decision
def __init__( def __init__(
self, self,
@@ -463,6 +468,7 @@ class ACStrategy(BaseStrategy):
# TODO: # TODO:
# 1. Supporting leverage the get_range_limit result from the decision # 1. Supporting leverage the get_range_limit result from the decision
# 2. Supporting alter_outer_trade_decision # 2. Supporting alter_outer_trade_decision
# 3. Supporting checking the availability of trade decision
def __init__( def __init__(
self, self,
lamb: float = 1e-6, lamb: float = 1e-6,
@@ -555,8 +561,7 @@ class ACStrategy(BaseStrategy):
if outer_trade_decision is not None: if outer_trade_decision is not None:
self.trade_amount = {} self.trade_amount = {}
# init the trade amount of order and predicted trade trend # init the trade amount of order and predicted trade trend
outer_order_generator = outer_trade_decision.generator() for order in outer_trade_decision.get_decision():
for order in outer_order_generator:
self.trade_amount[order.stock_id] = order.amount self.trade_amount[order.stock_id] = order.amount
def generate_trade_decision(self, execute_result=None): def generate_trade_decision(self, execute_result=None):
@@ -564,8 +569,6 @@ class ACStrategy(BaseStrategy):
trade_step = self.trade_calendar.get_trade_step() trade_step = self.trade_calendar.get_trade_step()
# get the total count of trading step # get the total count of trading step
trade_len = self.trade_calendar.get_trade_len() trade_len = self.trade_calendar.get_trade_len()
# update outer trade decision
self.outer_trade_decision.update(self.trade_calendar)
# update the order amount # update the order amount
if execute_result is not None: if execute_result is not None:
@@ -575,8 +578,7 @@ class ACStrategy(BaseStrategy):
trade_start_time, trade_end_time = self.trade_calendar.get_step_time(trade_step) trade_start_time, trade_end_time = self.trade_calendar.get_step_time(trade_step)
pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1) pred_start_time, pred_end_time = self.trade_calendar.get_step_time(trade_step, shift=1)
order_list = [] order_list = []
outer_order_generator = self.outer_trade_decision.generator(only_enable=True) for order in self.outer_trade_decision.get_decision():
for order in outer_order_generator:
# if not tradable, continue # if not tradable, continue
if not self.trade_exchange.is_stock_tradable( if not self.trade_exchange.is_stock_tradable(
stock_id=order.stock_id, start_time=trade_start_time, end_time=trade_end_time stock_id=order.stock_id, start_time=trade_start_time, end_time=trade_end_time
@@ -638,14 +640,16 @@ class ACStrategy(BaseStrategy):
class RandomOrderStrategy(BaseStrategy): class RandomOrderStrategy(BaseStrategy):
def __init__(
def __init__(self, self,
index_range: Tuple[int, int], # The range is closed on both left and right. index_range: Tuple[int, int], # The range is closed on both left and right.
sample_ratio: float = 1., sample_ratio: float = 1.0,
volume_ratio: float = 0.01, volume_ratio: float = 0.01,
market: str = "all", market: str = "all",
*args, direction: int = Order.BUY,
**kwargs): *args,
**kwargs,
):
""" """
Parameters Parameters
---------- ----------
@@ -667,9 +671,12 @@ class RandomOrderStrategy(BaseStrategy):
self.sample_ratio = sample_ratio self.sample_ratio = sample_ratio
self.volume_ratio = volume_ratio self.volume_ratio = volume_ratio
self.market = market self.market = market
self.direction = direction
exch: Exchange = self.common_infra.get("trade_exchange") exch: Exchange = self.common_infra.get("trade_exchange")
# TODO: this can't be online # TODO: this can't be online
self.volume = D.features(D.instruments(market), ["Mean(Ref($volume, 1), 10)"], start_time=exch.start_time, end_time=exch.end_time) self.volume = D.features(
D.instruments(market), ["Mean(Ref($volume, 1), 10)"], start_time=exch.start_time, end_time=exch.end_time
)
self.volume_df = self.volume.iloc[:, 0].unstack() self.volume_df = self.volume.iloc[:, 0].unstack()
def generate_trade_decision(self, execute_result=None): def generate_trade_decision(self, execute_result=None):
@@ -677,15 +684,15 @@ class RandomOrderStrategy(BaseStrategy):
step_time_start, step_time_end = self.trade_calendar.get_step_time(trade_step) step_time_start, step_time_end = self.trade_calendar.get_step_time(trade_step)
order_list = [] order_list = []
for direction in Order.SELL, Order.BUY: if step_time_start in self.volume_df:
if step_time_start in self.volume_df: for stock_id, volume in self.volume_df[step_time_start].dropna().sample(frac=self.sample_ratio).items():
for stock_id, volume in self.volume_df[step_time_start].dropna().sample(frac=self.sample_ratio).items(): order_list.append(
order_list.append( self.common_infra.get("trade_exchange").create_order(
self.common_infra.get("trade_exchange").create_order( code=stock_id,
code=stock_id, amount=volume * self.volume_ratio,
amount=volume * self.volume_ratio, start_time=step_time_start,
start_time=step_time_start, end_time=step_time_end,
end_time=step_time_end, direction=self.direction,
direction=direction, # 1 for buy )
)) )
return TradeDecisionWO(order_list, self, self.index_range) return TradeDecisionWO(order_list, self, self.index_range)

2
qlib/data/data.py
View File

@@ -213,7 +213,7 @@ class InstrumentProvider(abc.ABC, ProviderBackendMixin):
self.backend = kwargs.get("backend", {}) self.backend = kwargs.get("backend", {})
@staticmethod @staticmethod
def instruments(market: Union[List, str]="all", filter_pipe: Union[List, None]=None): def instruments(market: Union[List, str] = "all", filter_pipe: Union[List, None] = None):
"""Get the general config dictionary for a base market adding several dynamic filters. """Get the general config dictionary for a base market adding several dynamic filters.
Parameters Parameters

4
qlib/strategy/base.py
View File

@@ -85,7 +85,9 @@ class BaseStrategy:
""" """
raise NotImplementedError("generate_trade_decision is not implemented!") raise NotImplementedError("generate_trade_decision is not implemented!")
def update_trade_decision(self, trade_decision: BaseTradeDecision, trade_calendar: TradeCalendarManager) -> Union[BaseTradeDecision, None]: def update_trade_decision(
self, trade_decision: BaseTradeDecision, trade_calendar: TradeCalendarManager
) -> Union[BaseTradeDecision, None]:
""" """
update trade decision in each step of inner execution, this method enable all order update trade decision in each step of inner execution, this method enable all order

1
qlib/utils/resam.py
View File

@@ -9,6 +9,7 @@ from . import lazy_sort_index
from ..config import C from ..config import C
from .time import Freq, cal_sam_minute from .time import Freq, cal_sam_minute
def resam_calendar(calendar_raw: np.ndarray, freq_raw: str, freq_sam: str) -> np.ndarray: def resam_calendar(calendar_raw: np.ndarray, freq_raw: str, freq_sam: str) -> np.ndarray:
""" """
Resample the calendar with frequency freq_raw into the calendar with frequency freq_sam Resample the calendar with frequency freq_raw into the calendar with frequency freq_sam

29
qlib/utils/time.py
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@@ -14,7 +14,7 @@ import functools
@functools.lru_cache(maxsize=240) @functools.lru_cache(maxsize=240)
def get_min_cal(shift: int=0) -> List[time]: def get_min_cal(shift: int = 0) -> List[time]:
""" """
get the minute level calendar in day period get the minute level calendar in day period
@@ -30,8 +30,9 @@ def get_min_cal(shift: int=0) -> List[time]:
""" """
cal = [] cal = []
for ts in list(pd.date_range("9:30", "11:29", freq="1min") - pd.Timedelta(minutes=shift)) +\ for ts in list(pd.date_range("9:30", "11:29", freq="1min") - pd.Timedelta(minutes=shift)) + list(
list(pd.date_range("13:00", "14:59", freq="1min") - pd.Timedelta(minutes=shift)): pd.date_range("13:00", "14:59", freq="1min") - pd.Timedelta(minutes=shift)
):
cal.append(ts.time()) cal.append(ts.time())
return cal return cal
@@ -115,7 +116,7 @@ def get_day_min_idx_range(start: str, end: str, freq: str) -> Tuple[int, int]:
start = pd.Timestamp(start).time() start = pd.Timestamp(start).time()
end = pd.Timestamp(end).time() end = pd.Timestamp(end).time()
freq = Freq(freq) freq = Freq(freq)
in_day_cal = Freq.MIN_CAL[::freq.count] in_day_cal = Freq.MIN_CAL[:: freq.count]
left_idx = bisect.bisect_left(in_day_cal, start) left_idx = bisect.bisect_left(in_day_cal, start)
right_idx = bisect.bisect_right(in_day_cal, end) - 1 right_idx = bisect.bisect_right(in_day_cal, end) - 1
return left_idx, right_idx return left_idx, right_idx
@@ -141,15 +142,19 @@ def cal_sam_minute(x: pd.Timestamp, sam_minutes: int) -> pd.Timestamp:
""" """
cal = get_min_cal(C.min_data_shift)[::sam_minutes] cal = get_min_cal(C.min_data_shift)[::sam_minutes]
idx = bisect.bisect_right(cal, x.time()) - 1 idx = bisect.bisect_right(cal, x.time()) - 1
date, new_time = x.date(), cal[idx] date, new_time = x.date(), cal[idx]
return pd.Timestamp( return pd.Timestamp(
datetime(date.year, datetime(
month=date.month, date.year,
day=date.day, month=date.month,
hour=new_time.hour, day=date.day,
minute=new_time.minute, hour=new_time.hour,
second=new_time.second, minute=new_time.minute,
microsecond=new_time.microsecond)) second=new_time.second,
microsecond=new_time.microsecond,
)
)
if __name__ == "__main__": if __name__ == "__main__":
print(get_day_min_idx_range("8:30", "14:59", "10min")) print(get_day_min_idx_range("8:30", "14:59", "10min"))