nirs4all.controllers.transforms.y_transformer module

class nirs4all.controllers.transforms.y_transformer.YTransformerMixinController[source]

Bases: OperatorController

Controller for applying sklearn TransformerMixin operators to targets (y) instead of features (X).

Triggered by the “y_processing” keyword and applies transformations to target data, fitting on train targets and transforming all target data.

Supports both single transformers and chained transformers (list syntax):

  • Single: {“y_processing”: StandardScaler()}

  • Chained: {“y_processing”: [StandardScaler, QuantileTransformer(n_quantiles=30)]}

When using chained transformers, each transformer is applied sequentially, with proper ancestry tracking and individual artifact persistence for prediction mode.

execute(step_info: ParsedStep, dataset: SpectroDataset, context: ExecutionContext, runtime_context: RuntimeContext, source: int = -1, mode: str = 'train', loaded_binaries: Any = None, prediction_store: Any = None) → Tuple[ExecutionContext, List[Any]][source]

Execute transformer(s) on dataset targets, fitting on train targets and transforming all targets.

Supports both single transformers and chained transformers (list). Each transformer is applied sequentially, with proper ancestry tracking.

Parameters:

  • step_info – Parsed step containing operator and metadata

  • dataset – Dataset containing targets to transform

  • context – Pipeline context with partition information

  • runtime_context – Runtime context containing infrastructure components

  • source – Source index (not used for target processing)

  • mode – Execution mode (“train”, “predict”, or “explain”)

  • loaded_binaries – Pre-loaded fitted transformers for predict/explain mode

  • prediction_store – Not used for y_processing

Returns:

Tuple of (updated_context, fitted_transformers_list)

classmethod matches(step: Any, operator: Any, keyword: str) → bool[source]

Match if keyword is ‘y_processing’ and operator is TransformerMixin or list thereof.

Parameters:

  • step – Original step configuration

  • operator – Parsed operator (TransformerMixin instance, class, or list)

  • keyword – Step keyword

Returns:

True if this controller should handle the step

priority: int = 5
classmethod supports_prediction_mode() → bool[source]

Y transformers should not execute during prediction mode.

classmethod use_multi_source() → bool[source]

Check if the operator supports multi-source datasets.