mirror of
https://github.com/webclinic017/drift.git
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Mark Aron Szulyovszky
2606639cc2
* fix(Labelling): didn't forward shift forward returns previously, introduced major lookahead bias * fix(Baseline): use the same config
53 lines
1.5 KiB
Python
53 lines
1.5 KiB
Python
import pandas as pd
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from data_loader.types import ForwardReturnSeries
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from labeling.types import EventsDataFrame
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from typing import Callable
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import numpy as np
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def create_forward_returns(series: pd.Series, period: int) -> ForwardReturnSeries:
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assert period > 0
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indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=period)
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return series.rolling(window=indexer).sum().shift(-1)
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def purge_overlapping_events(events: EventsDataFrame) -> EventsDataFrame:
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events = events.copy()
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indicies_to_remove = []
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last_event_end = events.iloc[0]["start"]
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for index, row in events.iterrows():
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if row["start"] < last_event_end:
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indicies_to_remove.append(index)
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else:
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last_event_end = row["end"]
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events.drop(indicies_to_remove, inplace=True)
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return events
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def discretize_binary(x):
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return 1 if x > 0 else -1
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def discretize_binary_zero_one(x):
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return 1 if x > 0 else 0
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def discretize_threeway(x):
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return 0 if x == 0 else 1 if x > 0 else -1
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def discretize_threeway_threshold(threshold: float) -> Callable:
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def discretize(current_value):
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lower_threshold = -threshold
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upper_threshold = threshold
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if np.isnan(current_value):
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return np.nan
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elif current_value <= lower_threshold:
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return -1
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elif current_value > lower_threshold and current_value < upper_threshold:
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return 0
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else:
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return 1
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return discretize
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