Source code for skcriteria.preprocessing._preprocessing_base

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# License: BSD-3 (
# Copyright (c) 2016-2021, Cabral, Juan; Luczywo, Nadia
# Copyright (c) 2022, 2023, 2024 QuatroPe
# All rights reserved.

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"""Core functionalities to create transformers."""

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import abc

from ..core import DecisionMatrix, SKCMethodABC
from ..utils import doc_inherit

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# SKCTransformer ABC
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[docs] class SKCTransformerABC(SKCMethodABC): """Abstract class for all transformer in scikit-criteria.""" _skcriteria_dm_type = "transformer" _skcriteria_abstract_class = True @abc.abstractmethod def _transform_data(self, **kwargs): """Apply the transformation logic to the decision matrix parameters. Parameters ---------- kwargs: The decision matrix as separated parameters. Returns ------- :py:class:`dict` A dictionary with all the values of the decision matrix transformed. """ raise NotImplementedError()
[docs] def transform(self, dm): """Perform transformation on `dm`. Parameters ---------- dm: :py:class:`` The decision matrix to transform. Returns ------- :py:class:`` Transformed decision matrix. """ data = dm.to_dict() transformed_data = self._transform_data(**data) transformed_dm = DecisionMatrix.from_mcda_data(**transformed_data) return transformed_dm
# ============================================================================= # MATRIX & WEIGHTS TRANSFORMER # =============================================================================
[docs] class SKCMatrixAndWeightTransformerABC(SKCTransformerABC): """Transform weights and matrix together or independently. The Transformer that implements this abstract class can be configured to transform `weights`, `matrix` or `both` so only that part of the DecisionMatrix is altered. This abstract class require to redefine ``_transform_weights`` and ``_transform_matrix``, instead of ``_transform_data``. """ _skcriteria_abstract_class = True _skcriteria_parameters = ["target"] _TARGET_WEIGHTS = "weights" _TARGET_MATRIX = "matrix" _TARGET_BOTH = "both" def __init__(self, target): if target not in ( self._TARGET_MATRIX, self._TARGET_WEIGHTS, self._TARGET_BOTH, ): raise ValueError( f"'target' can only be '{self._TARGET_WEIGHTS}', " f"'{self._TARGET_MATRIX}' or '{self._TARGET_BOTH}', " f"found '{target}'" ) self._target = target @property def target(self): """Determine which part of the DecisionMatrix will be transformed.""" return self._target @abc.abstractmethod def _transform_weights(self, weights): """Execute the transform method over the weights. Parameters ---------- weights: :py:class:`numpy.ndarray` The weights to transform. Returns ------- :py:class:`numpy.ndarray` The transformed weights. """ raise NotImplementedError() @abc.abstractmethod def _transform_matrix(self, matrix): """Execute the transform method over the matrix. Parameters ---------- matrix: :py:class:`numpy.ndarray` The decision matrix to transform Returns ------- :py:class:`numpy.ndarray` The transformed matrix. """ raise NotImplementedError() @doc_inherit(SKCTransformerABC._transform_data) def _transform_data(self, matrix, weights, **kwargs): transformed_mtx = matrix transformed_weights = weights if self._target in (self._TARGET_MATRIX, self._TARGET_BOTH): transformed_mtx = self._transform_matrix(matrix) if self._target in (self._TARGET_WEIGHTS, self._TARGET_BOTH): transformed_weights = self._transform_weights(weights) kwargs.update( matrix=transformed_mtx, weights=transformed_weights, dtypes=None ) return kwargs