

'''simple docstring'''

from scipy.stats import pearsonr

import datasets


A_       						=							"\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that each dataset is normally distributed. Like other correlation coefficients, this one varies between -1 and +1 with 0 implying no correlation. Correlations of -1 or +1 imply an exact linear relationship. Positive correlations imply that as x increases, so does y. Negative correlations imply that as x increases, y decreases.\nThe p-value roughly indicates the probability of an uncorrelated system producing datasets that have a Pearson correlation at least as extreme as the one computed from these datasets.\n"


A_       						=							"\nArgs:\n    predictions (`list` of `int`): Predicted class labels, as returned by a model.\n    references (`list` of `int`): Ground truth labels.\n    return_pvalue (`boolean`): If `True`, returns the p-value, along with the correlation coefficient. If `False`, returns only the correlation coefficient. Defaults to `False`.\n\nReturns:\n    pearsonr (`float`): Pearson correlation coefficient. Minimum possible value is -1. Maximum possible value is 1. Values of 1 and -1 indicate exact linear positive and negative relationships, respectively. A value of 0 implies no correlation.\n    p-value (`float`): P-value, which roughly indicates the probability of an The p-value roughly indicates the probability of an uncorrelated system producing datasets that have a Pearson correlation at least as extreme as the one computed from these datasets. Minimum possible value is 0. Maximum possible value is 1. Higher values indicate higher probabilities.\n\nExamples:\n\n    Example 1-A simple example using only predictions and references.\n        >>> pearsonr_metric = datasets.load_metric(\"pearsonr\")\n        >>> results = pearsonr_metric.compute(predictions=[10, 9, 2.5, 6, 4], references=[1, 2, 3, 4, 5])\n        >>> print(round(results['pearsonr'], 2))\n        -0.74\n\n    Example 2-The same as Example 1, but that also returns the `p-value`.\n        >>> pearsonr_metric = datasets.load_metric(\"pearsonr\")\n        >>> results = pearsonr_metric.compute(predictions=[10, 9, 2.5, 6, 4], references=[1, 2, 3, 4, 5], return_pvalue=True)\n        >>> print(sorted(list(results.keys())))\n        ['p-value', 'pearsonr']\n        >>> print(round(results['pearsonr'], 2))\n        -0.74\n        >>> print(round(results['p-value'], 2))\n        0.15\n"


A_       						=							"\n@article{2020SciPy-NMeth,\nauthor  = {Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E. and\n      Haberland, Matt and Reddy, Tyler and Cournapeau, David and\n      Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and\n      Bright, Jonathan and {van der Walt}, St{\'e}fan J. and\n      Brett, Matthew and Wilson, Joshua and Millman, K. Jarrod and\n      Mayorov, Nikolay and Nelson, Andrew R. J. and Jones, Eric and\n      Kern, Robert and Larson, Eric and Carey, C J and\n      Polat, Ilhan and Feng, Yu and Moore, Eric W. and\n      {VanderPlas}, Jake and Laxalde, Denis and Perktold, Josef and\n      Cimrman, Robert and Henriksen, Ian and Quintero, E. A. and\n      Harris, Charles R. and Archibald, Anne M. and\n      Ribeiro, Antonio H. and Pedregosa, Fabian and\n      {van Mulbregt}, Paul and {SciPy 1.0 Contributors}},\ntitle   = {{{SciPy} 1.0: Fundamental Algorithms for Scientific\n      Computing in Python}},\njournal = {Nature Methods},\nyear    = {2020},\nvolume  = {17},\npages   = {261--272},\nadsurl  = {https://rdcu.be/b08Wh},\ndoi = {10.1038/s41592-019-0686-2},\n}\n"





@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION	,  _KWARGS_DESCRIPTION						)
class 							_snake_case (       datasets.Metric						):
   def     __UpperCamelCase						( self			:      str							):
     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.pearsonr.html"]     ,)







   def     __UpperCamelCase						( self			:      Optional[Any]     ,SCREAMING_SNAKE_CASE__			:      Any     ,SCREAMING_SNAKE_CASE__			:      int     ,SCREAMING_SNAKE_CASE__			:      List[Any]=False							):
     if return_pvalue:
       SCREAMING_SNAKE_CASE:List[Any]						      =					pearsonr(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)
       return {"pearsonr": results[0], "p-value": results[1]}
     else:
       return {"pearsonr": float(pearsonr(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)[0]							)}









'''simple docstring'''

from importlib import import_module

from .logging import get_logger


A_       						=							get_logger(__name__)





class 							_snake_case :
   def __init__( self			:      Dict     ,SCREAMING_SNAKE_CASE__			:      Any     ,SCREAMING_SNAKE_CASE__			:      Dict=None							):
     SCREAMING_SNAKE_CASE:Any						      =					attrs or []
     if module is not None:
       for key in module.__dict__:
         if key in attrs or not key.startswith("__"							):
           setattr(self     ,SCREAMING_SNAKE_CASE__     ,getattr(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)							)
     SCREAMING_SNAKE_CASE:Any						      =					module._original_module if isinstance(SCREAMING_SNAKE_CASE__     ,_PatchedModuleObj							) else module





class 							_snake_case :
   _A       :     Any       =					[]
   def __init__( self			:      Any     ,SCREAMING_SNAKE_CASE__			:      List[str]     ,SCREAMING_SNAKE_CASE__			:      str     ,SCREAMING_SNAKE_CASE__			:      str     ,SCREAMING_SNAKE_CASE__			:      Optional[Any]=None							):
     SCREAMING_SNAKE_CASE:Any						      =					obj
     SCREAMING_SNAKE_CASE:Any						      =					target
     SCREAMING_SNAKE_CASE:Union[str, Any]						      =					new
     SCREAMING_SNAKE_CASE:Any						      =					target.split("."							)[0]
     SCREAMING_SNAKE_CASE:str						      =					{}
     SCREAMING_SNAKE_CASE:List[Any]						      =					attrs or []
   def __enter__( self			:      Tuple							):
     *SCREAMING_SNAKE_CASE      ,    SCREAMING_SNAKE_CASE:int						      =					self.target.split("."							)

     # Patch modules:
     # it's used to patch attributes of submodules like "os.path.join";
     # in this case we need to patch "os" and "os.path"

     for i in range(len(SCREAMING_SNAKE_CASE__							)							):
       try:
         SCREAMING_SNAKE_CASE:int						      =					import_module(".".join(submodules[: i + 1]							)							)
       except ModuleNotFoundError:
         continue
       # We iterate over all the globals in self.obj in case we find "os" or "os.path"
       for attr in self.obj.__dir__():
         SCREAMING_SNAKE_CASE:str						      =					getattr(self.obj     ,SCREAMING_SNAKE_CASE__							)
         # We don't check for the name of the global, but rather if its value *is* "os" or "os.path".
         # This allows to patch renamed modules like "from os import path as ospath".
         if obj_attr is submodule or (
             (isinstance(SCREAMING_SNAKE_CASE__     ,_PatchedModuleObj							) and obj_attr._original_module is submodule)
         ):
           SCREAMING_SNAKE_CASE:Union[str, Any]						      =					obj_attr
           # patch at top level
           setattr(self.obj     ,SCREAMING_SNAKE_CASE__     ,_PatchedModuleObj(SCREAMING_SNAKE_CASE__     ,attrs=self.attrs							)							)
           SCREAMING_SNAKE_CASE:int						      =					getattr(self.obj     ,SCREAMING_SNAKE_CASE__							)
           # construct lower levels patches
           for key in submodules[i + 1 :]:
             setattr(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__     ,_PatchedModuleObj(getattr(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)     ,attrs=self.attrs							)							)
             SCREAMING_SNAKE_CASE:Dict						      =					getattr(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__							)
           # finally set the target attribute
           setattr(SCREAMING_SNAKE_CASE__     ,SCREAMING_SNAKE_CASE__     ,self.new							)

        # Patch attribute itself:
        # it's used for builtins like "open",
        # and also to patch "os.path.join" we may also need to patch "join"
        # itself if it was imported as "from os.path import join".

     if submodules:  # if it's an attribute of a submodule like "os.path.join"
       try:
         SCREAMING_SNAKE_CASE:Any						      =					getattr(import_module(".".join(SCREAMING_SNAKE_CASE__							)							)     ,SCREAMING_SNAKE_CASE__							)
       except (AttributeError, ModuleNotFoundError):
         return
       # We iterate over all the globals in self.obj in case we find "os.path.join"
       for attr in self.obj.__dir__():
         # We don't check for the name of the global, but rather if its value *is* "os.path.join".
         # This allows to patch renamed attributes like "from os.path import join as pjoin".
         if getattr(self.obj     ,SCREAMING_SNAKE_CASE__							) is attr_value:
           SCREAMING_SNAKE_CASE:Union[str, Any]						      =					getattr(self.obj     ,SCREAMING_SNAKE_CASE__							)
           setattr(self.obj     ,SCREAMING_SNAKE_CASE__     ,self.new							)
     elif target_attr in globals()["__builtins__"]:  # if it'a s builtin like "open"
       SCREAMING_SNAKE_CASE:int						      =					globals()["__builtins__"][target_attr]
       setattr(self.obj     ,SCREAMING_SNAKE_CASE__     ,self.new							)
     else:
       raise RuntimeError(F'''Tried to patch attribute {target_attr} instead of a submodule.'''							)
   def __exit__( self			:      List[Any]     ,*SCREAMING_SNAKE_CASE__			:      Union[str, Any]							):
     for attr in list(self.original							):
       setattr(self.obj     ,SCREAMING_SNAKE_CASE__     ,self.original.pop(SCREAMING_SNAKE_CASE__							)							)
   def     __UpperCamelCase						( self			:      Optional[int]							):
     self.__enter__()
     self._active_patches.append(self							)







   def     __UpperCamelCase						( self			:      Dict							):
     try:
       self._active_patches.remove(self							)
     except ValueError:
       # If the patch hasn't been started this will fail
       return None

     return self.__exit__()






