energy_fault_detector.data_preprocessing.angle_transformer

class AngleTransformer(angles=None, trust_bad_angles=False)[source]

Bases: DataTransformer

Transforms features containing angles to their sine and cosine values. Currently, assumes all angles are in degrees.

angles

List of feature names (str) which are angles that need to be transformed.

trust_bad_angles

If True angle features that neither suit the value range (-180, 180) nor (0, 360) will be transformed the same way as valid angles. If False, out of range angle features will be dropped.

fit(x, y=None)[source]

Sets feature names in and out and detects value ranges of angle features.

Return type:

AngleTransformer

get_feature_names_out(input_features=None)[source]

Returns the list of feature names output by the angle transformation step.

Return type:

List[str]

inverse_transform(x)[source]

Get the angles based on their sine values and drop the sine/cosine values. NOTE: if sine/cosine values are out of possible range (-1, 1), values below -1 are set to -1 and values above 1 to 1.

Return type:

DataFrame

set_fit_request(*, x: bool | None | str = '$UNCHANGED$') → AngleTransformer

Request metadata passed to the fit method.

Note that this method is only relevant if enable_metadata_routing=True (see sklearn.set_config()). Please see User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to fit if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to fit.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Note

This method is only relevant if this estimator is used as a sub-estimator of a meta-estimator, e.g. used inside a Pipeline. Otherwise it has no effect.

Parameters

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in fit.

Returns

selfobject

The updated object.

set_inverse_transform_request(*, x: bool | None | str = '$UNCHANGED$') → AngleTransformer

Request metadata passed to the inverse_transform method.

Note that this method is only relevant if enable_metadata_routing=True (see sklearn.set_config()). Please see User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to inverse_transform if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to inverse_transform.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Note

This method is only relevant if this estimator is used as a sub-estimator of a meta-estimator, e.g. used inside a Pipeline. Otherwise it has no effect.

Parameters

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in inverse_transform.

Returns

selfobject

The updated object.

set_transform_request(*, x: bool | None | str = '$UNCHANGED$') → AngleTransformer

Request metadata passed to the transform method.

Note that this method is only relevant if enable_metadata_routing=True (see sklearn.set_config()). Please see User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to transform if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to transform.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Note

This method is only relevant if this estimator is used as a sub-estimator of a meta-estimator, e.g. used inside a Pipeline. Otherwise it has no effect.

Parameters

xstr, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED

Metadata routing for x parameter in transform.

Returns

selfobject

The updated object.

transform(x)[source]

Transforms the angle angles to sine and cosine values.

Return type:

DataFrame