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75157c6285
* feat(Labeling): purge overlapping events, sort dataframe at loading time * fix(Linter): ran * refactor(Labeling): moved purge_overlapping_events one abstraction level higher * fix(Data): renamed class * fix(Data): corrected parameter name * fix(Config): parameters * fix(Data): fixed path * fix(Data): uncommented required code * feat(EventFilters): use vol based CUSUM * fix(Config): only retrain every 2000 samples * fix(Config): filter out even more events * fix(Inference): added remove_overlapping_events * refactor(Types): simplified type hierarchy
30 lines
741 B
Python
30 lines
741 B
Python
from data_loader.types import ReturnSeries, ForwardReturnSeries
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from abc import ABC, abstractmethod
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import pandas as pd
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import pandera as pa
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from pandera.typing import DataFrame, Series
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class EventFilter(ABC):
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@abstractmethod
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def get_event_start_times(self, returns: ReturnSeries) -> pd.DatetimeIndex:
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raise NotImplementedError
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class EventSchema(pa.SchemaModel):
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start: Series[pd.Timestamp]
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end: Series[pd.Timestamp]
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label: Series[int]
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returns: Series[float]
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EventsDataFrame = DataFrame[EventSchema]
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class EventLabeller(ABC):
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@abstractmethod
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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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raise NotImplementedError
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