energy_fault_detector.core.data_transformer

class DataTransformer(*args, **kwargs)

Bases: BaseEstimator, TransformerMixin, SaveLoadMixin, ABC

DataTransformer template.

abstractmethod fit(x, y=None)

Fit the preprocessor with training data. Should set attributes feature_names_in_ and n_features_in_. If columns are selected/dropped, should also set feature_names_out_ and columns_dropped_.

Parameters:

x (DataFrame) – pandas dataframe with input data
y (Series) – (optional) labels indicating whether sample is normal (True) or anomalous (False).

Return type:

DataTransformer

abstractmethod get_feature_names_out(input_features=None)

Get output feature names for transformation.

Return type:: List[str]

Returns: feature_names_out : list/np array of str objects.

abstractmethod inverse_transform(x)

Implement inverse transform method

Parameters:: x (DataFrame) – input data.
Return type:: DataFrame

abstractmethod transform(x)

Implement transform method.

Parameters:: x (DataFrame) – input data.
Return type:: DataFrame