
from scipy.stats import spearmanr

import datasets


lowerCamelCase__    :		Union[str, Any]          =   """
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.
"""

lowerCamelCase__    :		int          =   """
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
"""

lowerCamelCase__    :		str          =   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       _snake_case   (	datasets.Metric							):


 def      lowercase__     (					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      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_=False):


   '''simple docstring'''




   lowercase__  :   List[str]    		=      spearmanr(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
   if return_pvalue:
     return {"spearmanr": results[0], "spearmanr_pvalue": results[1]}
   else:
     return {"spearmanr": results[0]}






from __future__ import annotations

from collections.abc import Iterator
from typing import Any



class       _snake_case   :


 def __init__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Any    		=      data
   lowercase__  :   Node | None    		=      None



class       _snake_case   :


 def __init__(					self):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      None
   lowercase__  :   int    		=      None


 def __iter__(					self):


   '''simple docstring'''




   lowercase__  :   List[str]    		=      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(SCREAMING_SNAKE_CASE_) for item in iter(self))


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   self.insert_nth(len(self)					,  SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   self.insert_nth(0					,  SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




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


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.delete_nth(0)


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.delete_nth(len(self) - 1)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_ = 0):


   '''simple docstring'''




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



 def      lowercase__     (					self):


   '''simple docstring'''




   return len(self) == 0

def 		UpperCamelCase	(      )		->	None:


  '''simple docstring'''






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

  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(lowercase_   ) == i
    circular_linked_list.insert_nth(lowercase_ , i + 1   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 6   )   )

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

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

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

  assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
     import doctest

     doctest.testmod()






