






"""simple docstring"""







from __future__ import annotations

from collections.abc import Iterator
from typing import Any


class    __UpperCAmelCase:




						"""simple docstring"""




						def __init__(       self	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				Any=	data
												lowercase__    :				Node | None=	None


class    __UpperCAmelCase:




						"""simple docstring"""




						def __init__(       self      ):
												'''simple docstring'''
												lowercase__    :				List[str]=	None
												lowercase__    :				int=	None




						def __iter__(       self      ):
												'''simple docstring'''
												lowercase__    :				Any=	self.head
												while self.head:
																		yield node.data
																		lowercase__    :				str=	node.next
																		if node == self.head:
																								break




						def __len__(       self      ):
												'''simple docstring'''
												return sum(1 for _ in self      )




						def __repr__(       self      ):
												'''simple docstring'''
												return "->".join(str(snake_case__      ) for item in iter(self      )      )




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												self.insert_nth(len(self      )	,  snake_case__      )




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												self.insert_nth(0	,  snake_case__      )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												if index < 0 or index > len(self      ):
																		raise IndexError("list index out of range."      )
												lowercase__    :				Optional[Any]=	Node(snake_case__      )
												if self.head is None:
																		lowercase__    :				Tuple=	new_node  # first node points itself
																		lowercase__    :				str=	new_node
												elif index == 0:  # insert at head
																		lowercase__    :				Dict=	self.head
																		lowercase__    :				int=	new_node
												else:
																		lowercase__    :				Dict=	self.head
																		for _ in range(index - 1      ):
																								lowercase__    :				Any=	temp.next
																		lowercase__    :				str=	temp.next
																		lowercase__    :				Dict=	new_node
																		if index == len(self      ) - 1:  # insert at tail
																								lowercase__    :				int=	new_node




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												return self.delete_nth(0      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												return self.delete_nth(len(self      ) - 1      )




						def 		UpperCAmelCase_	(       self	,  snake_case__ = 0      ):
												'''simple docstring'''
												if not 0 <= index < len(self      ):
																		raise IndexError("list index out of range."      )
												lowercase__    :				int=	self.head
												if self.head == self.tail:  # just one node
																		lowercase__    :				Union[str, Any]=	None
												elif index == 0:  # delete head node
																		lowercase__    :				Tuple=	self.tail.next.next
																		lowercase__    :				Union[str, Any]=	self.head.next
												else:
																		lowercase__    :				Union[str, Any]=	self.head
																		for _ in range(index - 1      ):
																								lowercase__    :				Dict=	temp.next
																		lowercase__    :				List[str]=	temp.next
																		lowercase__    :				Optional[Any]=	temp.next.next
																		if index == len(self      ) - 1:  # delete at tail
																								lowercase__    :				Optional[Any]=	temp
												return delete_node.data




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												return len(self      ) == 0





def 						lowercase__()    ->None:




						"""simple docstring"""



						lowercase__    :				Dict=	CircularLinkedList()
						assert len(A						) == 0
						assert circular_linked_list.is_empty() is True
						assert str(A						) == ""

						try:
												circular_linked_list.delete_front()
												raise AssertionError  # This should not happen
						except IndexError:
												assert True  # This should happen

						try:
												circular_linked_list.delete_tail()
												raise AssertionError  # This should not happen
						except IndexError:
												assert True  # This should happen

						try:
												circular_linked_list.delete_nth(-1						)
												raise AssertionError
						except IndexError:
												assert True

						try:
												circular_linked_list.delete_nth(0						)
												raise AssertionError
						except IndexError:
												assert True

						assert circular_linked_list.is_empty() is True
						for i in range(5						):
												assert len(A						) == i
												circular_linked_list.insert_nth(A ,		i + 1						)
						assert str(A						) == "->".join(str(A						) for i in range(1 ,		6						)						)

						circular_linked_list.insert_tail(6						)
						assert str(A						) == "->".join(str(A						) for i in range(1 ,		7						)						)
						circular_linked_list.insert_head(0						)
						assert str(A						) == "->".join(str(A						) for i in range(0 ,		7						)						)

						assert circular_linked_list.delete_front() == 0
						assert circular_linked_list.delete_tail() == 6
						assert str(A						) == "->".join(str(A						) for i in range(1 ,		6						)						)
						assert circular_linked_list.delete_nth(2						) == 3

						circular_linked_list.insert_nth(2 ,		3						)
						assert str(A						) == "->".join(str(A						) for i in range(1 ,		6						)						)

						assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
			import doctest

			doctest.testmod()














"""simple docstring"""







from scipy.stats import spearmanr

import datasets


a			:    Dict				 =		"""
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correlation.
Positive correlations imply that as data in dataset x increases, so
does data in dataset y. Negative correlations imply that as x increases,
y decreases. Correlations of -1 or +1 imply an exact monotonic relationship.

Unlike the Pearson correlation, the Spearman correlation does not
assume that both datasets are normally distributed.

The p-value roughly indicates the probability of an uncorrelated system
producing datasets that have a Spearman correlation at least as extreme
as the one computed from these datasets. The p-values are not entirely
reliable but are probably reasonable for datasets larger than 500 or so.
"""

a			:    List[Any]				 =		"""
Args:
    predictions (`List[float]`): Predicted labels, as returned by a model.
    references (`List[float]`): Ground truth labels.
    return_pvalue (`bool`): If `True`, returns the p-value. If `False`, returns
            only the spearmanr score. Defaults to `False`.
Returns:
    spearmanr (`float`): Spearman correlation coefficient.
    p-value (`float`): p-value. **Note**: is only returned if `return_pvalue=True` is input.
Examples:
    Example 1:
        >>> spearmanr_metric = datasets.load_metric(\"spearmanr\")
        >>> results = spearmanr_metric.compute(references=[1, 2, 3, 4, 5], predictions=[10, 9, 2.5, 6, 4])
        >>> print(results)
        {'spearmanr': -0.7}

    Example 2:
        >>> spearmanr_metric = datasets.load_metric(\"spearmanr\")
        >>> results = spearmanr_metric.compute(references=[1, 2, 3, 4, 5],
        ...                                     predictions=[10, 9, 2.5, 6, 4],
        ...                                     return_pvalue=True)
        >>> print(results['spearmanr'])
        -0.7
        >>> print(round(results['spearmanr_pvalue'], 2))
        0.19
"""

a			:    int				 =		r"""\
@book{kokoska2000crc,
  title={CRC standard probability and statistics tables and formulae},
  author={Kokoska, Stephen and Zwillinger, Daniel},
  year={2000},
  publisher={Crc Press}
}
@article{2020SciPy-NMeth,
  author  = {Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E. and
            Haberland, Matt and Reddy, Tyler and Cournapeau, David and
            Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and
            Bright, Jonathan and {van der Walt}, St{\'e}fan J. and
            Brett, Matthew and Wilson, Joshua and Millman, K. Jarrod and
            Mayorov, Nikolay and Nelson, Andrew R. J. and Jones, Eric and
            Kern, Robert and Larson, Eric and Carey, C J and
            Polat, {\.I}lhan and Feng, Yu and Moore, Eric W. and
            {VanderPlas}, Jake and Laxalde, Denis and Perktold, Josef and
            Cimrman, Robert and Henriksen, Ian and Quintero, E. A. and
            Harris, Charles R. and Archibald, Anne M. and
            Ribeiro, Ant{\^o}nio H. and Pedregosa, Fabian and
            {van Mulbregt}, Paul and {SciPy 1.0 Contributors}},
  title   = {{{SciPy} 1.0: Fundamental Algorithms for Scientific
            Computing in Python}},
  journal = {Nature Methods},
  year    = {2020},
  volume  = {17},
  pages   = {261--272},
  adsurl  = {https://rdcu.be/b08Wh},
  doi     = {10.1038/s41592-019-0686-2},
}
"""


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




						"""simple docstring"""




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												return datasets.MetricInfo(
												    description=_DESCRIPTION	,  citation=_CITATION	,  inputs_description=_KWARGS_DESCRIPTION	,  features=datasets.Features(
												        {
												            "predictions": datasets.Value("float"      ),
												            "references": datasets.Value("float"      ),
												        }      )	,  reference_urls=["https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.spearmanr.html"]	,  )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__	,  snake_case__=False      ):
												'''simple docstring'''
												lowercase__    :				Optional[int]=	spearmanr(snake_case__	,  snake_case__      )
												if return_pvalue:
																		return {"spearmanr": results[0], "spearmanr_pvalue": results[1]}
												else:
																		return {"spearmanr": results[0]}






