mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-27 18:57:55 +00:00
Mark Aron Szulyovszky
43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
from ..types import EventLabeller, EventsDataFrame, ReturnSeries
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import pandas as pd
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from .utils import create_forward_returns
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from typing import Callable
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from .utils import discretize_binary
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class FixedTimeHorionTwoClassEventLabeller(EventLabeller):
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time_horizon: int
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def __init__(self, time_horizon: int):
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self.time_horizon = time_horizon
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def label_events(
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self, event_start_times: pd.DatetimeIndex, returns: ReturnSeries
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) -> EventsDataFrame:
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forward_returns = create_forward_returns(returns, self.time_horizon)
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cutoff_point = returns.index[-self.time_horizon]
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event_start_times = event_start_times[event_start_times < cutoff_point]
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event_candidates = forward_returns[event_start_times]
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def get_class_binary(x: float) -> int:
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return -1 if x <= 0.0 else 1
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labels = event_candidates.map(get_class_binary)
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events = pd.DataFrame(
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{
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"start": event_start_times,
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"end": event_start_times + pd.Timedelta(minutes=self.time_horizon * 5),
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"label": labels,
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"returns": forward_returns[event_start_times],
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}
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)
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return events
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def get_labels(self) -> list[int]:
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return [-1, 1]
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def get_discretize_function(self) -> Callable:
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return discretize_binary
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