hyperactive.integrations.sklearn.utils

Complexity

Total Complexity

4

Size/Duplication

Total Lines	39
Duplicated Lines	0 %

Importance

Changes

0

2 Functions

Rating	Name	Duplication	Size	Complexity
A	_estimator_has()	0	12	2
A	_check_refit()	0	4	2

# Author: Simon Blanke
# Email: simon.blanke@yahoo.com
# License: MIT License


from sklearn.utils.validation import (
    indexable,
    _check_method_params,
    check_is_fitted,
)

# NOTE Implementations of following methods from:
# https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/model_selection/_search.py
# Tag: 1.5.1


def _check_refit(search_cv, attr):
    if not search_cv.refit:
        raise AttributeError(
            f"This {type(search_cv).__name__} instance was initialized with "
            f"`refit=False`. {attr} is available only after refitting on the best "
            "parameters. You can refit an estimator manually using the "
            "`best_params_` attribute"
        )


def _estimator_has(attr):
    def check(self):
        _check_refit(self, attr)
        if hasattr(self, "best_estimator_"):
            # raise an AttributeError if `attr` does not exist
            getattr(self.best_estimator_, attr)
            return True
        # raise an AttributeError if `attr` does not exist
        getattr(self.estimator, attr)
        return True

    return check