labeling/labellers/utils.py

import pandas as pd
from data_loader.types import ForwardReturnSeries


def create_forward_returns(series: pd.Series, period: int) -> ForwardReturnSeries:
    assert period > 0
    indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=period)

    forward_returns = series.rolling(window=indexer).sum()
    return forward_returns
feat(Project): use SKLearn models directly, removed custom ensembling, use 5 minute data, batch inference, numba cusum filter (#192 ) 2022-02-17 16:36:35 +01:00			`import pandas as pd`
			`from data_loader.types import ForwardReturnSeries`

chore(Linter): reformatted code with black (#211 ) 2022-02-17 19:22:17 +01:00
feat(Project): use SKLearn models directly, removed custom ensembling, use 5 minute data, batch inference, numba cusum filter (#192 ) 2022-02-17 16:36:35 +01:00			`def create_forward_returns(series: pd.Series, period: int) -> ForwardReturnSeries:`
			`assert period > 0`
			`indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=period)`
chore(Linter): reformatted code with black (#211 ) 2022-02-17 19:22:17 +01:00
feat(Project): use SKLearn models directly, removed custom ensembling, use 5 minute data, batch inference, numba cusum filter (#192 ) 2022-02-17 16:36:35 +01:00			`forward_returns = series.rolling(window=indexer).sum()`
chore(Linter): reformatted code with black (#211 ) 2022-02-17 19:22:17 +01:00			`return forward_returns`