





import numpy as np

import datasets


_A					:				Union[str, Any]				=			"""
Compute the Mahalanobis Distance

Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.
It was introduced by Prof. P. C. Mahalanobis in 1936
and has been used in various statistical applications ever since
[source: https://www.machinelearningplus.com/statistics/mahalanobis-distance/]
"""

_A					:				Optional[Any]				=			"""\
@article{de2000mahalanobis,
  title={The mahalanobis distance},
  author={De Maesschalck, Roy and Jouan-Rimbaud, Delphine and Massart, D{\'e}sir{\'e} L},
  journal={Chemometrics and intelligent laboratory systems},
  volume={50},
  number={1},
  pages={1--18},
  year={2000},
  publisher={Elsevier}
}
"""

_A					:				Union[str, Any]				=			"""
Args:
    X: List of datapoints to be compared with the `reference_distribution`.
    reference_distribution: List of datapoints from the reference distribution we want to compare to.
Returns:
    mahalanobis: The Mahalonobis distance for each datapoint in `X`.
Examples:

    >>> mahalanobis_metric = datasets.load_metric(\"mahalanobis\")
    >>> results = mahalanobis_metric.compute(reference_distribution=[[0, 1], [1, 0]], X=[[0, 1]])
    >>> print(results)
    {'mahalanobis': array([0.5])}
"""



@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION			,     _KWARGS_DESCRIPTION    )
class 					__snake_case	(  datasets.Metric    ):


    '''simple docstring'''







    def  lowercase_					(       self     ):





        '''simple docstring'''

        return datasets.MetricInfo(
            description=_DESCRIPTION   ,				citation=_CITATION   ,				inputs_description=_KWARGS_DESCRIPTION   ,				features=datasets.Features(
                {
                    '''X''': datasets.Sequence(datasets.Value('''float'''   ,				id='''sequence'''     )   ,				id='''X'''     ),
                }     )   ,				)




    def  lowercase_					(       self   ,				A_   ,				A_     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			np.array(A_     )
        SCREAMING_SNAKE_CASE__											=			np.array(A_     )

        # Assert that arrays are 2D
        if len(X.shape     ) != 2:
            raise ValueError('''Expected `X` to be a 2D vector'''     )
        if len(reference_distribution.shape     ) != 2:
            raise ValueError('''Expected `reference_distribution` to be a 2D vector'''     )
        if reference_distribution.shape[0] < 2:
            raise ValueError(
                '''Expected `reference_distribution` to be a 2D vector with more than one element in the first dimension'''     )

        # Get mahalanobis distance for each prediction
        SCREAMING_SNAKE_CASE__											=			X - np.mean(A_     )
        SCREAMING_SNAKE_CASE__											=			np.cov(reference_distribution.T     )
        try:
            SCREAMING_SNAKE_CASE__											=			np.linalg.inv(A_     )
        except np.linalg.LinAlgError:
            SCREAMING_SNAKE_CASE__											=			np.linalg.pinv(A_     )
        SCREAMING_SNAKE_CASE__											=			np.dot(A_   ,				A_     )
        SCREAMING_SNAKE_CASE__											=			np.dot(A_   ,				X_minus_mu.T     ).diagonal()

        return {"mahalanobis": mahal_dist}







import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline


@pytest.mark.integration
def 							__snake_case							(    )				->						Any:
    with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT	):
        with pytest.raises(lowerCAmelCase_	):
            requests.request('''GET''' ,							'''https://huggingface.co'''	)
        with pytest.raises(requests.exceptions.ConnectTimeout	):
            requests.request('''GET''' ,							'''https://huggingface.co''' ,							timeout=1.0	)


@pytest.mark.integration
def 							__snake_case							(    )				->						int:
    with offline(OfflineSimulationMode.CONNECTION_FAILS	):
        with pytest.raises(requests.exceptions.ConnectionError	):
            requests.request('''GET''' ,							'''https://huggingface.co'''	)



def 							__snake_case							(    )				->						List[Any]:
    with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1	):
        with pytest.raises(lowerCAmelCase_	):
            http_head('''https://huggingface.co'''	)
