gpytorchwrapper.src.data.data_transform

Functions

transform(train_x, train_y, test_x, test_y, ...)	Applies transformations to training and test datasets based on configuration.
transform_data(x, transformer[, columns])	Transform the input data using the selected transformer

gpytorchwrapper.src.data.data_transform.transform(train_x: DataFrame, train_y: DataFrame, test_x: DataFrame | None, test_y: DataFrame | None, transform_conf: TransformConf) → tuple[DataFrame, DataFrame, DataFrame, DataFrame, object | None, object | None] | tuple[DataFrame, DataFrame, None, None, object, object]

Applies transformations to training and test datasets based on configuration.

Parameters:

• train_x (pandas.DataFrame) – Input features for the training dataset.

• train_y (pandas.DataFrame) – Output targets for the training dataset.

• test_x (pandas.DataFrame or None) – Input features for the test dataset, or None if not provided.

• test_y (pandas.DataFrame or None) – Output targets for the test dataset, or None if not provided.

• transform_conf (TransformConf) – Configuration object containing settings for input and output transformations.

Returns:

A tuple containing: - Transformed training input features (pandas.DataFrame) - Transformed test input features (pandas.DataFrame or None) - Transformed training targets (pandas.DataFrame) - Transformed test targets (pandas.DataFrame or None) - Input transformer object used or None - Output transformer object used or None

Return type:

tuple

gpytorchwrapper.src.data.data_transform.transform_data(x: DataFrame, transformer: object, columns: list[int] | None = None) → DataFrame | tuple[DataFrame, object]

Transform the input data using the selected transformer

Parameters:

• x (pd.DataFrame) – The input data

• transformer (object) – The selected transformer

• columns (list, optional) – The columns on which the transformer has to operate

Returns:

• x (pd.DataFrame) – The transformed input data

• transformer (object) – The fitted transformer