_OneSegmentChangePointsTrendTransform¶

class _OneSegmentChangePointsTrendTransform(in_column: str, change_point_model: ruptures.base.BaseEstimator, detrend_model: Type[sklearn.base.RegressorMixin], **change_point_model_predict_params)[source]¶

Bases: etna.transforms.base.Transform

_OneSegmentChangePointsTransform subtracts multiple linear trend from series.

Init _OneSegmentChangePointsTrendTransform.

Parameters

in_column (str) – name of column to apply transform to
change_point_model (ruptures.base.BaseEstimator) – model to get trend change points
detrend_model (Type[sklearn.base.RegressorMixin]) – model to get trend in data
change_point_model_predict_params – params for change_point_model.predict method

Inherited-members

Methods

`fit`(df)	Fit OneSegmentChangePointsTransform: find trend change points in `df`, fit detrend models with data from intervals of stable trend.
`fit_transform`(df)	May be reimplemented.
`inverse_transform`(df)	Split df to intervals of stable trend according to previous change point detection and add trend to each one.
`transform`(df)	Split df to intervals of stable trend and subtract trend from each one.

fit(df: pandas.core.frame.DataFrame) → etna.transforms.decomposition.change_points_trend._OneSegmentChangePointsTrendTransform[source]¶

Fit OneSegmentChangePointsTransform: find trend change points in df, fit detrend models with data from intervals of stable trend.

Parameters: df (pandas.core.frame.DataFrame) – one segment dataframe indexed with timestamp
Return type: etna.transforms.decomposition.change_points_trend._OneSegmentChangePointsTrendTransform

inverse_transform(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame[source]¶

Split df to intervals of stable trend according to previous change point detection and add trend to each one.

Parameters: df (pandas.core.frame.DataFrame) – one segment dataframe to turn trend back
Returns: df – df with restored trend in in_column
Return type: pd.DataFrame

transform(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame[source]¶

Split df to intervals of stable trend and subtract trend from each one.

Parameters: df (pandas.core.frame.DataFrame) – one segment dataframe to subtract trend
Returns: detrended df – df with detrended in_column series
Return type: pd.DataFrame