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https://github.com/webclinic017/drift.git
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Mark Aron Szulyovszky
567cd5e9f0
* refactor(Evaluate): print out accuracy, f1, etc. for the final & meta predictions, separated out evaluation step * fix(Linter): ran * fix(Tests): syntax change * fix(Inference): runs now again * fix(Linter): ran
37 lines
929 B
Python
37 lines
929 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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from typing import Callable
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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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def get_labels(self) -> list[int]:
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raise NotImplementedError
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def get_discretize_function(self) -> Callable:
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raise NotImplementedError
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