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https://github.com/microsoft/qlib.git
synced 2026-07-04 03:21:00 +08:00
Add more friendly index range by timing
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@@ -368,11 +368,17 @@ class NestedExecutor(BaseExecutor):
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break
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sub_cal: TradeCalendarManager = self.inner_executor.trade_calendar
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# NOTE: make sure get_start_end_idx is after `self._update_trade_decision`
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start_idx, end_idx = get_start_end_idx(sub_cal, trade_decision)
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if not self._align_range_limit or start_idx <= sub_cal.get_trade_step() <= end_idx:
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# if force align the range limit, skip the steps outside the decision range limit
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_inner_trade_decision = self.inner_strategy.generate_trade_decision(_inner_execute_result)
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_inner_trade_decision: BaseTradeDecision = self.inner_strategy.generate_trade_decision(
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_inner_execute_result
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)
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trade_decision.mod_inner_decision(_inner_trade_decision) # propagate part of decision information
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# NOTE sub_cal.get_cur_step_time() must be called before collect_data in case of step shifting
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decision_list.append((_inner_trade_decision, *sub_cal.get_cur_step_time()))
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@@ -3,10 +3,11 @@
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# TODO: rename it with decision.py
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from __future__ import annotations
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from enum import IntEnum
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from qlib.utils.time import concat_date_time
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from qlib.log import get_module_logger
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# try to fix circular imports when enabling type hints
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from typing import TYPE_CHECKING
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from typing import Callable, TYPE_CHECKING
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if TYPE_CHECKING:
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from qlib.strategy.base import BaseStrategy
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@@ -164,6 +165,35 @@ class OrderHelper:
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)
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class IndexRangeByTime:
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"""This is a helper function for make decisions"""
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def __init__(self, start_time: str, end_time: str):
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"""
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This is a callable class.
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**NOTE**:
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- It is designed for minute-bar for intraday trading!!!!!
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- Both start_time and end_time are **closed** in the range
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Parameters
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----------
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start_time : str
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e.g. "9:30"
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end_time : str
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e.g. "14:30"
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"""
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self.start_time = pd.Timestamp(start_time).time()
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self.end_time = pd.Timestamp(end_time).time()
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def __call__(self, trade_calendar: TradeCalendarManager) -> Tuple[int, int]:
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start = trade_calendar.start_time
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val_start, val_end = concat_date_time(start.date(), self.start_time), concat_date_time(
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start.date(), self.end_time
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)
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return trade_calendar.get_range_idx(val_start, val_end)
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class BaseTradeDecision:
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"""
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Trade decisions ara made by strategy and executed by exeuter
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@@ -180,16 +210,54 @@ class BaseTradeDecision:
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2. Same as `case 1.3`
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"""
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def __init__(self, strategy: BaseStrategy, idx_range: Tuple[int, int] = None):
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def __init__(self, strategy: BaseStrategy, idx_range: Union[Tuple[int, int], Callable] = None):
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"""
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Parameters
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----------
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strategy : BaseStrategy
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The strategy who make the decision
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idx_range: Union[Tuple[int, int], Callable] (optional)
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The index range for underlying strategy.
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Here are two examples of idx_range for each type
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1) Tuple[int, int]
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start_index and end_index of the underlying factor(both sides are closed)
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2) Callable
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.. code-block:: python
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def idx_range(time_per_step: str) -> Tuple[int, int]:
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# time_per_step is the strategy's time_per_step (not inner strategy. It's the `self` strategy in
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# `self._idx_range` )
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# e.g.
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# For example, strategy A with 30min each step and strategy B with 1min each step
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# strategy A's will use "30min" when calling `idx_range`.
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"""
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self.strategy = strategy
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self.total_step = None # upper strategy has no knowledge about the sub executor before `_init_sub_trading`
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self.idx_range = idx_range
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self._idx_range = idx_range
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@staticmethod
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def _calc_idx_range(
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idx_range: Union[Tuple[int, int], Callable], inner_calendar: TradeCalendarManager = None
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) -> Tuple[int, int]:
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"""calculate index range for `idx_range` in different cases"""
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if idx_range is None:
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# not set, return nothing
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return None, None
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elif isinstance(idx_range, tuple):
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return idx_range
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elif isinstance(idx_range, Callable):
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if inner_calendar is None:
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# time_per_step is a required parameter for `def idx_range`
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return None, None
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else:
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return idx_range(inner_calendar)
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else:
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raise NotImplementedError(f"This type of input is not supported")
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def get_decision(self) -> List[object]:
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"""
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@@ -212,7 +280,7 @@ class BaseTradeDecision:
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"""
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Be called at the **start** of each step.
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This function is designn for following purpose
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This function is design for following purpose
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1) Leave a hook for the strategy who make `self` decision to update the decision itself
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2) Update some information from the inner executor calendar
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@@ -230,12 +298,6 @@ class BaseTradeDecision:
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"""
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# purpose 1)
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self.total_step = trade_calendar.get_trade_len()
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if self.idx_range is not None:
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logger = get_module_logger("decision")
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start_idx, end_idx = self.idx_range
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if start_idx < 0 or end_idx >= self.total_step:
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logger.warning(f"{self.idx_range} go beyound the total_step({self.total_step}), it will be clipped")
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self.idx_range = max(0, start_idx), min(self.total_step - 1, end_idx)
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# purpose 2)
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return self.strategy.update_trade_decision(self, trade_calendar)
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@@ -245,9 +307,28 @@ class BaseTradeDecision:
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return the expected step range for limiting the decision execution time
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Both left and right are **closed**
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if no available _idx_range, `default_value` will be returned
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It is only used in `NestedExecutor`
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- The outmost strategy will not follow any range limit (but it may give range_limit)
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- The inner most strategy's range_limit will be useless due to atomic executors don't have such
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features.
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**NOTE**:
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1) This function must be called after `self.update` in following cases(ensured by NestedExecutor):
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- user relies on the auto-clip feature of `self.update`
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2) This function will be called after _init_sub_trading in NestedExecutor.
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Parameters
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----------
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**kwargs:
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{"default_value": <default_value>}
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# using dict is for distinguish no value provided or None provided
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{
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"default_value": <default_value>, # using dict is for distinguish no value provided or None provided
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"inner_calendar": <trade calendar of inner strategy>
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# because the range limit will control the step range of inner strategy, inner calendar will be a
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# important parameter when _idx_range is callable
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}
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Returns
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-------
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@@ -258,15 +339,32 @@ class BaseTradeDecision:
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NotImplementedError:
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If the following criteria meet
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1) the decision can't provide a unified start and end
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2) default_value is None
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2) default_value is not provided
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"""
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if self.idx_range is None:
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# get index
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_start_idx, _end_idx = self._calc_idx_range(self._idx_range, inner_calendar=kwargs.get("inner_calendar"))
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if _start_idx is None or _end_idx is None:
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# handle case without decision
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# TODO: time range in the order should be checked.
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# _start_idx and _end_idx should be used instead of _idx_range
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# because it is possible that no limitation when _idx_range is callable and return None
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if "default_value" in kwargs:
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return kwargs["default_value"]
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else:
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# Default to get full index
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raise NotImplementedError(f"The decision didn't provide an index range")
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return self.idx_range
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else:
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# clip index
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if getattr(self, "total_step", None) is not None:
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# if `self.update` is called.
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# Then the _start_idx, _end_idx should be clipped
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if _start_idx < 0 or _end_idx >= self.total_step:
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logger = get_module_logger("decision")
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logger.warning(f"{self._idx_range} go beyoud the total_step({self.total_step}), it will be clipped")
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_start_idx, _end_idx = max(0, _start_idx), min(self.total_step - 1, _end_idx)
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return _start_idx, _end_idx
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def empty(self) -> bool:
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for obj in self.get_decision():
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@@ -278,6 +376,27 @@ class BaseTradeDecision:
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return True
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return True
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def mod_inner_decision(self, inner_trade_decision: BaseTradeDecision):
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"""
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This method will be called on the inner_trade_decision after it is generated.
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`inner_trade_decision` will be changed **inplaced**.
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Motivation of the `mod_inner_decision`
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- Leave a hook for outer decision to affact the decision generated by the inner strategy
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- e.g. the outmost strategy generate a time range for trading. But the upper layer can only affact the
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nearest layer in the original design. With `mod_inner_decision`, the decision can passed through multiple
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layers
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Parameters
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----------
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inner_trade_decision : BaseTradeDecision
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"""
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# base class provide a default behaviour to modify inner_trade_decision
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# callable _idx_range should be propagated when inner _idx_range is not set
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if isinstance(self._idx_range, Callable) and inner_trade_decision._idx_range is None:
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inner_trade_decision._idx_range = self._idx_range
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class EmptyTradeDecision(BaseTradeDecision):
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def empty(self) -> bool:
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@@ -298,7 +417,7 @@ class TradeDecisionWO(BaseTradeDecision):
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return self.order_list
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def __repr__(self) -> str:
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return f"strategy: {self.strategy}; idx_range: {self.idx_range}; order_list[{len(self.order_list)}]"
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return f"strategy: {self.strategy}; idx_range: {self._idx_range}; order_list[{len(self.order_list)}]"
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# TODO: the orders below need to be discussed ------------------------------------
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@@ -372,7 +372,7 @@ class Indicator:
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raise NotImplementedError(f"This type of input is not supported")
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# if there is no stock data during the time period
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if(price_s is None):
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if price_s is None:
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return None, None
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# NOTE: there are some zeros in the trading price. These cases are known meaningless
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@@ -456,7 +456,7 @@ class Indicator:
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trade_exchange=trade_exchange,
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pa_config=pa_config,
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)
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if((bp_tmp is not None) and (bv_tmp is not None)):
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if (bp_tmp is not None) and (bv_tmp is not None):
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bp_new[inst], bv_new[inst] = bp_tmp, bv_tmp
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else:
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bp_new[inst], bv_new[inst] = pr, v
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@@ -1,6 +1,7 @@
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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from __future__ import annotations
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import bisect
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from typing import Union, TYPE_CHECKING, Tuple, Union, List, Set
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if TYPE_CHECKING:
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@@ -118,6 +119,33 @@ class TradeCalendarManager:
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"""Get the start_time and end_time for trading"""
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return self.start_time, self.end_time
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# helper functions
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def get_range_idx(self, start_time: pd.Timestamp, end_time: pd.Timestamp) -> Tuple[int, int]:
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"""
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get the range index which involve start_time~end_time (both sides are closed)
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Parameters
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----------
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start_time : pd.Timestamp
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end_time : pd.Timestamp
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Returns
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-------
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Tuple[int, int]:
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the index of the range. **the left and right are closed**
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"""
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left, right = (
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bisect.bisect_right(self._calendar, start_time) - 1,
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bisect.bisect_right(self._calendar, end_time) - 1,
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)
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left -= self.start_index
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right -= self.start_index
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def clip(idx):
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return min(max(0, idx), self.trade_len - 1)
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return clip(left), clip(right)
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def __repr__(self) -> str:
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return f"{self.start_time}[{self.start_index}]~{self.end_time}[{self.end_index}]: [{self.trade_step}/{self.trade_len}]"
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@@ -201,6 +229,6 @@ def get_start_end_idx(trade_calendar: TradeCalendarManager, outer_trade_decision
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start index and end index
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"""
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try:
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return outer_trade_decision.get_range_limit()
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return outer_trade_decision.get_range_limit(inner_calendar=trade_calendar)
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except NotImplementedError:
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return 0, trade_calendar.get_trade_len() - 1
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@@ -4,7 +4,7 @@
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Time related utils are compiled in this script
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"""
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import bisect
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from datetime import datetime, time
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from datetime import datetime, time, date
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from typing import List, Tuple
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import re
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from numpy import append
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@@ -122,6 +122,20 @@ def get_day_min_idx_range(start: str, end: str, freq: str) -> Tuple[int, int]:
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return left_idx, right_idx
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def concat_date_time(date_obj: date, time_obj: time) -> pd.Timestamp:
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return pd.Timestamp(
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datetime(
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date_obj.year,
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month=date_obj.month,
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day=date_obj.day,
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hour=time_obj.hour,
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minute=time_obj.minute,
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second=time_obj.second,
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microsecond=time_obj.microsecond,
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)
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)
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def cal_sam_minute(x: pd.Timestamp, sam_minutes: int) -> pd.Timestamp:
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"""
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align the minute-level data to a down sampled calendar
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@@ -143,17 +157,7 @@ def cal_sam_minute(x: pd.Timestamp, sam_minutes: int) -> pd.Timestamp:
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cal = get_min_cal(C.min_data_shift)[::sam_minutes]
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idx = bisect.bisect_right(cal, x.time()) - 1
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date, new_time = x.date(), cal[idx]
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return pd.Timestamp(
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datetime(
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date.year,
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month=date.month,
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day=date.day,
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hour=new_time.hour,
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minute=new_time.minute,
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second=new_time.second,
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microsecond=new_time.microsecond,
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)
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)
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return concat_date_time(date, new_time)
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if __name__ == "__main__":
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